>>don't talk mhm, >>Okay, thing is my presentation on coherent nonlinear dynamics and combinatorial optimization. This is going to be a talk to introduce an approach we're taking to the analysis of the performance of coherent using machines. So let me start with a brief introduction to easing optimization. The easing model represents a set of interacting magnetic moments or spins the total energy given by the expression shown at the bottom left of this slide. Here, the signal variables are meditate binary values. The Matrix element J. I. J. Represents the interaction, strength and signed between any pair of spins. I. J and A Chive represents a possible local magnetic field acting on each thing. The easing ground state problem is to find an assignment of binary spin values that achieves the lowest possible value of total energy. And an instance of the easing problem is specified by giving numerical values for the Matrix J in Vector H. Although the easy model originates in physics, we understand the ground state problem to correspond to what would be called quadratic binary optimization in the field of operations research and in fact, in terms of computational complexity theory, it could be established that the easing ground state problem is np complete. Qualitatively speaking, this makes the easing problem a representative sort of hard optimization problem, for which it is expected that the runtime required by any computational algorithm to find exact solutions should, as anatomically scale exponentially with the number of spends and for worst case instances at each end. Of course, there's no reason to believe that the problem instances that actually arrives in practical optimization scenarios are going to be worst case instances. And it's also not generally the case in practical optimization scenarios that we demand absolute optimum solutions. Usually we're more interested in just getting the best solution we can within an affordable cost, where costs may be measured in terms of time, service fees and or energy required for a computation. This focuses great interest on so called heuristic algorithms for the easing problem in other NP complete problems which generally get very good but not guaranteed optimum solutions and run much faster than algorithms that are designed to find absolute Optima. To get some feeling for present day numbers, we can consider the famous traveling salesman problem for which extensive compilations of benchmarking data may be found online. A recent study found that the best known TSP solver required median run times across the Library of Problem instances That scaled is a very steep route exponential for end up to approximately 4500. This gives some indication of the change in runtime scaling for generic as opposed the worst case problem instances. Some of the instances considered in this study were taken from a public library of T SPS derived from real world Veil aside design data. This feels I TSP Library includes instances within ranging from 131 to 744,710 instances from this library with end between 6880 13,584 were first solved just a few years ago in 2017 requiring days of run time and a 48 core to King hurts cluster, while instances with and greater than or equal to 14,233 remain unsolved exactly by any means. Approximate solutions, however, have been found by heuristic methods for all instances in the VLS i TSP library with, for example, a solution within 0.14% of a no lower bound, having been discovered, for instance, with an equal 19,289 requiring approximately two days of run time on a single core of 2.4 gigahertz. Now, if we simple mindedly extrapolate the root exponential scaling from the study up to an equal 4500, we might expect that an exact solver would require something more like a year of run time on the 48 core cluster used for the N equals 13,580 for instance, which shows how much a very small concession on the quality of the solution makes it possible to tackle much larger instances with much lower cost. At the extreme end, the largest TSP ever solved exactly has an equal 85,900. This is an instance derived from 19 eighties VLSI design, and it's required 136 CPU. Years of computation normalized to a single cord, 2.4 gigahertz. But the 24 larger so called world TSP benchmark instance within equals 1,904,711 has been solved approximately within ophthalmology. Gap bounded below 0.474%. Coming back to the general. Practical concerns have applied optimization. We may note that a recent meta study analyzed the performance of no fewer than 37 heuristic algorithms for Max cut and quadratic pioneer optimization problems and found the performance sort and found that different heuristics work best for different problem instances selected from a large scale heterogeneous test bed with some evidence but cryptic structure in terms of what types of problem instances were best solved by any given heuristic. Indeed, their their reasons to believe that these results from Mexico and quadratic binary optimization reflected general principle of performance complementarity among heuristic optimization algorithms in the practice of solving heart optimization problems there. The cerise is a critical pre processing issue of trying to guess which of a number of available good heuristic algorithms should be chosen to tackle a given problem. Instance, assuming that any one of them would incur high costs to run on a large problem, instances incidence, making an astute choice of heuristic is a crucial part of maximizing overall performance. Unfortunately, we still have very little conceptual insight about what makes a specific problem instance, good or bad for any given heuristic optimization algorithm. This has certainly been pinpointed by researchers in the field is a circumstance that must be addressed. So adding this all up, we see that a critical frontier for cutting edge academic research involves both the development of novel heuristic algorithms that deliver better performance, with lower cost on classes of problem instances that are underserved by existing approaches, as well as fundamental research to provide deep conceptual insight into what makes a given problem in, since easy or hard for such algorithms. In fact, these days, as we talk about the end of Moore's law and speculate about a so called second quantum revolution, it's natural to talk not only about novel algorithms for conventional CPUs but also about highly customized special purpose hardware architectures on which we may run entirely unconventional algorithms for combinatorial optimization such as easing problem. So against that backdrop, I'd like to use my remaining time to introduce our work on analysis of coherent using machine architectures and associate ID optimization algorithms. These machines, in general, are a novel class of information processing architectures for solving combinatorial optimization problems by embedding them in the dynamics of analog, physical or cyber physical systems, in contrast to both MAWR traditional engineering approaches that build using machines using conventional electron ICS and more radical proposals that would require large scale quantum entanglement. The emerging paradigm of coherent easing machines leverages coherent nonlinear dynamics in photonic or Opto electronic platforms to enable near term construction of large scale prototypes that leverage post Simoes information dynamics, the general structure of of current CM systems has shown in the figure on the right. The role of the easing spins is played by a train of optical pulses circulating around a fiber optical storage ring. A beam splitter inserted in the ring is used to periodically sample the amplitude of every optical pulse, and the measurement results are continually read into a refugee A, which uses them to compute perturbations to be applied to each pulse by a synchronized optical injections. These perturbations, air engineered to implement the spin, spin coupling and local magnetic field terms of the easing Hamiltonian, corresponding to a linear part of the CME Dynamics, a synchronously pumped parametric amplifier denoted here as PPL and Wave Guide adds a crucial nonlinear component to the CIA and Dynamics as well. In the basic CM algorithm, the pump power starts very low and has gradually increased at low pump powers. The amplitude of the easing spin pulses behaviors continuous, complex variables. Who Israel parts which can be positive or negative, play the role of play the role of soft or perhaps mean field spins once the pump, our crosses the threshold for parametric self oscillation. In the optical fiber ring, however, the attitudes of the easing spin pulses become effectively Qantas ized into binary values while the pump power is being ramped up. The F P J subsystem continuously applies its measurement based feedback. Implementation of the using Hamiltonian terms, the interplay of the linear rised using dynamics implemented by the F P G A and the threshold conversation dynamics provided by the sink pumped Parametric amplifier result in the final state of the optical optical pulse amplitude at the end of the pump ramp that could be read as a binary strain, giving a proposed solution of the easing ground state problem. This method of solving easing problem seems quite different from a conventional algorithm that runs entirely on a digital computer as a crucial aspect of the computation is performed physically by the analog, continuous, coherent, nonlinear dynamics of the optical degrees of freedom. In our efforts to analyze CIA and performance, we have therefore turned to the tools of dynamical systems theory, namely, a study of modifications, the evolution of critical points and apologies of hetero clinic orbits and basins of attraction. We conjecture that such analysis can provide fundamental insight into what makes certain optimization instances hard or easy for coherent using machines and hope that our approach can lead to both improvements of the course, the AM algorithm and a pre processing rubric for rapidly assessing the CME suitability of new instances. Okay, to provide a bit of intuition about how this all works, it may help to consider the threshold dynamics of just one or two optical parametric oscillators in the CME architecture just described. We can think of each of the pulse time slots circulating around the fiber ring, as are presenting an independent Opio. We can think of a single Opio degree of freedom as a single, resonant optical node that experiences linear dissipation, do toe out coupling loss and gain in a pump. Nonlinear crystal has shown in the diagram on the upper left of this slide as the pump power is increased from zero. As in the CME algorithm, the non linear game is initially to low toe overcome linear dissipation, and the Opio field remains in a near vacuum state at a critical threshold. Value gain. Equal participation in the Popeo undergoes a sort of lazing transition, and the study states of the OPIO above this threshold are essentially coherent states. There are actually two possible values of the Opio career in amplitude and any given above threshold pump power which are equal in magnitude but opposite in phase when the OPI across the special diet basically chooses one of the two possible phases randomly, resulting in the generation of a single bit of information. If we consider to uncoupled, Opio has shown in the upper right diagram pumped it exactly the same power at all times. Then, as the pump power has increased through threshold, each Opio will independently choose the phase and thus to random bits are generated for any number of uncoupled. Oppose the threshold power per opio is unchanged from the single Opio case. Now, however, consider a scenario in which the two appeals air, coupled to each other by a mutual injection of their out coupled fields has shown in the diagram on the lower right. One can imagine that depending on the sign of the coupling parameter Alfa, when one Opio is lazing, it will inject a perturbation into the other that may interfere either constructively or destructively, with the feel that it is trying to generate by its own lazing process. As a result, when came easily showed that for Alfa positive, there's an effective ferro magnetic coupling between the two Opio fields and their collective oscillation threshold is lowered from that of the independent Opio case. But on Lee for the two collective oscillation modes in which the two Opio phases are the same for Alfa Negative, the collective oscillation threshold is lowered on Lee for the configurations in which the Opio phases air opposite. So then, looking at how Alfa is related to the J. I. J matrix of the easing spin coupling Hamiltonian, it follows that we could use this simplistic to a p o. C. I am to solve the ground state problem of a fair magnetic or anti ferro magnetic ankles to easing model simply by increasing the pump power from zero and observing what phase relation occurs as the two appeals first start delays. Clearly, we can imagine generalizing this story toe larger, and however the story doesn't stay is clean and simple for all larger problem instances. And to find a more complicated example, we only need to go to n equals four for some choices of J J for n equals, for the story remains simple. Like the n equals two case. The figure on the upper left of this slide shows the energy of various critical points for a non frustrated and equals, for instance, in which the first bifurcated critical point that is the one that I forget to the lowest pump value a. Uh, this first bifurcated critical point flows as symptomatically into the lowest energy easing solution and the figure on the upper right. However, the first bifurcated critical point flows to a very good but sub optimal minimum at large pump power. The global minimum is actually given by a distinct critical critical point that first appears at a higher pump power and is not automatically connected to the origin. The basic C am algorithm is thus not able to find this global minimum. Such non ideal behaviors needs to become more confident. Larger end for the n equals 20 instance, showing the lower plots where the lower right plot is just a zoom into a region of the lower left lot. It can be seen that the global minimum corresponds to a critical point that first appears out of pump parameter, a around 0.16 at some distance from the idiomatic trajectory of the origin. That's curious to note that in both of these small and examples, however, the critical point corresponding to the global minimum appears relatively close to the idiomatic projector of the origin as compared to the most of the other local minima that appear. We're currently working to characterize the face portrait topology between the global minimum in the antibiotic trajectory of the origin, taking clues as to how the basic C am algorithm could be generalized to search for non idiomatic trajectories that jump to the global minimum during the pump ramp. Of course, n equals 20 is still too small to be of interest for practical optimization applications. But the advantage of beginning with the study of small instances is that we're able reliably to determine their global minima and to see how they relate to the 80 about trajectory of the origin in the basic C am algorithm. In the smaller and limit, we can also analyze fully quantum mechanical models of Syrian dynamics. But that's a topic for future talks. Um, existing large scale prototypes are pushing into the range of in equals 10 to the 4 10 to 5 to six. So our ultimate objective in theoretical analysis really has to be to try to say something about CIA and dynamics and regime of much larger in our initial approach to characterizing CIA and behavior in the large in regime relies on the use of random matrix theory, and this connects to prior research on spin classes, SK models and the tap equations etcetera. At present, we're focusing on statistical characterization of the CIA ingredient descent landscape, including the evolution of critical points in their Eigen value spectra. As the pump power is gradually increased. We're investigating, for example, whether there could be some way to exploit differences in the relative stability of the global minimum versus other local minima. We're also working to understand the deleterious or potentially beneficial effects of non ideologies, such as a symmetry in the implemented these and couplings. Looking one step ahead, we plan to move next in the direction of considering more realistic classes of problem instances such as quadratic, binary optimization with constraints. Eso In closing, I should acknowledge people who did the hard work on these things that I've shown eso. My group, including graduate students Ed winning, Daniel Wennberg, Tatsuya Nagamoto and Atsushi Yamamura, have been working in close collaboration with Syria Ganguly, Marty Fair and Amir Safarini Nini, all of us within the Department of Applied Physics at Stanford University. On also in collaboration with the Oshima Moto over at NTT 55 research labs, Onda should acknowledge funding support from the NSF by the Coherent Easing Machines Expedition in computing, also from NTT five research labs, Army Research Office and Exxon Mobil. Uh, that's it. Thanks very much. >>Mhm e >>t research and the Oshie for putting together this program and also the opportunity to speak here. My name is Al Gore ism or Andy and I'm from Caltech, and today I'm going to tell you about the work that we have been doing on networks off optical parametric oscillators and how we have been using them for icing machines and how we're pushing them toward Cornum photonics to acknowledge my team at Caltech, which is now eight graduate students and five researcher and postdocs as well as collaborators from all over the world, including entity research and also the funding from different places, including entity. So this talk is primarily about networks of resonate er's, and these networks are everywhere from nature. For instance, the brain, which is a network of oscillators all the way to optics and photonics and some of the biggest examples or metal materials, which is an array of small resonate er's. And we're recently the field of technological photonics, which is trying thio implement a lot of the technological behaviors of models in the condensed matter, physics in photonics and if you want to extend it even further, some of the implementations off quantum computing are technically networks of quantum oscillators. So we started thinking about these things in the context of icing machines, which is based on the icing problem, which is based on the icing model, which is the simple summation over the spins and spins can be their upward down and the couplings is given by the JJ. And the icing problem is, if you know J I J. What is the spin configuration that gives you the ground state? And this problem is shown to be an MP high problem. So it's computational e important because it's a representative of the MP problems on NPR. Problems are important because first, their heart and standard computers if you use a brute force algorithm and they're everywhere on the application side. That's why there is this demand for making a machine that can target these problems, and hopefully it can provide some meaningful computational benefit compared to the standard digital computers. So I've been building these icing machines based on this building block, which is a degenerate optical parametric. Oscillator on what it is is resonator with non linearity in it, and we pump these resonate er's and we generate the signal at half the frequency of the pump. One vote on a pump splits into two identical photons of signal, and they have some very interesting phase of frequency locking behaviors. And if you look at the phase locking behavior, you realize that you can actually have two possible phase states as the escalation result of these Opio which are off by pie, and that's one of the important characteristics of them. So I want to emphasize a little more on that and I have this mechanical analogy which are basically two simple pendulum. But there are parametric oscillators because I'm going to modulate the parameter of them in this video, which is the length of the string on by that modulation, which is that will make a pump. I'm gonna make a muscular. That'll make a signal which is half the frequency of the pump. And I have two of them to show you that they can acquire these face states so they're still facing frequency lock to the pump. But it can also lead in either the zero pie face states on. The idea is to use this binary phase to represent the binary icing spin. So each opio is going to represent spin, which can be either is your pie or up or down. And to implement the network of these resonate er's, we use the time off blood scheme, and the idea is that we put impulses in the cavity. These pulses air separated by the repetition period that you put in or t r. And you can think about these pulses in one resonator, xaz and temporarily separated synthetic resonate Er's if you want a couple of these resonator is to each other, and now you can introduce these delays, each of which is a multiple of TR. If you look at the shortest delay it couples resonator wanted to 2 to 3 and so on. If you look at the second delay, which is two times a rotation period, the couple's 123 and so on. And if you have and minus one delay lines, then you can have any potential couplings among these synthetic resonate er's. And if I can introduce these modulators in those delay lines so that I can strength, I can control the strength and the phase of these couplings at the right time. Then I can have a program will all toe all connected network in this time off like scheme, and the whole physical size of the system scales linearly with the number of pulses. So the idea of opium based icing machine is didn't having these o pos, each of them can be either zero pie and I can arbitrarily connect them to each other. And then I start with programming this machine to a given icing problem by just setting the couplings and setting the controllers in each of those delight lines. So now I have a network which represents an icing problem. Then the icing problem maps to finding the face state that satisfy maximum number of coupling constraints. And the way it happens is that the icing Hamiltonian maps to the linear loss of the network. And if I start adding gain by just putting pump into the network, then the OPI ohs are expected to oscillate in the lowest, lowest lost state. And, uh and we have been doing these in the past, uh, six or seven years and I'm just going to quickly show you the transition, especially what happened in the first implementation, which was using a free space optical system and then the guided wave implementation in 2016 and the measurement feedback idea which led to increasing the size and doing actual computation with these machines. So I just want to make this distinction here that, um, the first implementation was an all optical interaction. We also had an unequal 16 implementation. And then we transition to this measurement feedback idea, which I'll tell you quickly what it iss on. There's still a lot of ongoing work, especially on the entity side, to make larger machines using the measurement feedback. But I'm gonna mostly focused on the all optical networks and how we're using all optical networks to go beyond simulation of icing Hamiltonian both in the linear and non linear side and also how we're working on miniaturization of these Opio networks. So the first experiment, which was the four opium machine, it was a free space implementation and this is the actual picture off the machine and we implemented a small and it calls for Mexico problem on the machine. So one problem for one experiment and we ran the machine 1000 times, we looked at the state and we always saw it oscillate in one of these, um, ground states of the icing laboratoria. So then the measurement feedback idea was to replace those couplings and the controller with the simulator. So we basically simulated all those coherent interactions on on FB g. A. And we replicated the coherent pulse with respect to all those measurements. And then we injected it back into the cavity and on the near to you still remain. So it still is a non. They're dynamical system, but the linear side is all simulated. So there are lots of questions about if this system is preserving important information or not, or if it's gonna behave better. Computational wars. And that's still ah, lot of ongoing studies. But nevertheless, the reason that this implementation was very interesting is that you don't need the end minus one delight lines so you can just use one. Then you can implement a large machine, and then you can run several thousands of problems in the machine, and then you can compare the performance from the computational perspective Looks so I'm gonna split this idea of opium based icing machine into two parts. One is the linear part, which is if you take out the non linearity out of the resonator and just think about the connections. You can think about this as a simple matrix multiplication scheme. And that's basically what gives you the icing Hambletonian modeling. So the optical laws of this network corresponds to the icing Hamiltonian. And if I just want to show you the example of the n equals for experiment on all those face states and the history Graham that we saw, you can actually calculate the laws of each of those states because all those interferences in the beam splitters and the delay lines are going to give you a different losses. And then you will see that the ground states corresponds to the lowest laws of the actual optical network. If you add the non linearity, the simple way of thinking about what the non linearity does is that it provides to gain, and then you start bringing up the gain so that it hits the loss. Then you go through the game saturation or the threshold which is going to give you this phase bifurcation. So you go either to zero the pie face state. And the expectation is that Theis, the network oscillates in the lowest possible state, the lowest possible loss state. There are some challenges associated with this intensity Durban face transition, which I'm going to briefly talk about. I'm also going to tell you about other types of non aerodynamics that we're looking at on the non air side of these networks. So if you just think about the linear network, we're actually interested in looking at some technological behaviors in these networks. And the difference between looking at the technological behaviors and the icing uh, machine is that now, First of all, we're looking at the type of Hamilton Ian's that are a little different than the icing Hamilton. And one of the biggest difference is is that most of these technological Hamilton Ian's that require breaking the time reversal symmetry, meaning that you go from one spin to in the one side to another side and you get one phase. And if you go back where you get a different phase, and the other thing is that we're not just interested in finding the ground state, we're actually now interesting and looking at all sorts of states and looking at the dynamics and the behaviors of all these states in the network. So we started with the simplest implementation, of course, which is a one d chain of thes resonate, er's, which corresponds to a so called ssh model. In the technological work, we get the similar energy to los mapping and now we can actually look at the band structure on. This is an actual measurement that we get with this associate model and you see how it reasonably how How? Well, it actually follows the prediction and the theory. One of the interesting things about the time multiplexing implementation is that now you have the flexibility of changing the network as you are running the machine. And that's something unique about this time multiplex implementation so that we can actually look at the dynamics. And one example that we have looked at is we can actually go through the transition off going from top A logical to the to the standard nontrivial. I'm sorry to the trivial behavior of the network. You can then look at the edge states and you can also see the trivial and states and the technological at states actually showing up in this network. We have just recently implement on a two D, uh, network with Harper Hofstadter model and when you don't have the results here. But we're one of the other important characteristic of time multiplexing is that you can go to higher and higher dimensions and keeping that flexibility and dynamics, and we can also think about adding non linearity both in a classical and quantum regimes, which is going to give us a lot of exotic, no classical and quantum, non innate behaviors in these networks. Yeah, So I told you about the linear side. Mostly let me just switch gears and talk about the nonlinear side of the network. And the biggest thing that I talked about so far in the icing machine is this face transition that threshold. So the low threshold we have squeezed state in these. Oh, pios, if you increase the pump, we go through this intensity driven phase transition and then we got the face stays above threshold. And this is basically the mechanism off the computation in these O pos, which is through this phase transition below to above threshold. So one of the characteristics of this phase transition is that below threshold, you expect to see quantum states above threshold. You expect to see more classical states or coherent states, and that's basically corresponding to the intensity off the driving pump. So it's really hard to imagine that it can go above threshold. Or you can have this friends transition happen in the all in the quantum regime. And there are also some challenges associated with the intensity homogeneity off the network, which, for example, is if one opioid starts oscillating and then its intensity goes really high. Then it's going to ruin this collective decision making off the network because of the intensity driven face transition nature. So So the question is, can we look at other phase transitions? Can we utilize them for both computing? And also can we bring them to the quantum regime on? I'm going to specifically talk about the face transition in the spectral domain, which is the transition from the so called degenerate regime, which is what I mostly talked about to the non degenerate regime, which happens by just tuning the phase of the cavity. And what is interesting is that this phase transition corresponds to a distinct phase noise behavior. So in the degenerate regime, which we call it the order state, you're gonna have the phase being locked to the phase of the pump. As I talked about non degenerate regime. However, the phase is the phase is mostly dominated by the quantum diffusion. Off the off the phase, which is limited by the so called shallow towns limit, and you can see that transition from the general to non degenerate, which also has distinct symmetry differences. And this transition corresponds to a symmetry breaking in the non degenerate case. The signal can acquire any of those phases on the circle, so it has a you one symmetry. Okay, and if you go to the degenerate case, then that symmetry is broken and you only have zero pie face days I will look at. So now the question is can utilize this phase transition, which is a face driven phase transition, and can we use it for similar computational scheme? So that's one of the questions that were also thinking about. And it's not just this face transition is not just important for computing. It's also interesting from the sensing potentials and this face transition, you can easily bring it below threshold and just operated in the quantum regime. Either Gaussian or non Gaussian. If you make a network of Opio is now, we can see all sorts off more complicated and more interesting phase transitions in the spectral domain. One of them is the first order phase transition, which you get by just coupling to Opio, and that's a very abrupt face transition and compared to the to the single Opio phase transition. And if you do the couplings right, you can actually get a lot of non her mission dynamics and exceptional points, which are actually very interesting to explore both in the classical and quantum regime. And I should also mention that you can think about the cup links to be also nonlinear couplings. And that's another behavior that you can see, especially in the nonlinear in the non degenerate regime. So with that, I basically told you about these Opio networks, how we can think about the linear scheme and the linear behaviors and how we can think about the rich, nonlinear dynamics and non linear behaviors both in the classical and quantum regime. I want to switch gear and tell you a little bit about the miniaturization of these Opio networks. And of course, the motivation is if you look at the electron ICS and what we had 60 or 70 years ago with vacuum tube and how we transition from relatively small scale computers in the order of thousands of nonlinear elements to billions of non elements where we are now with the optics is probably very similar to 70 years ago, which is a table talk implementation. And the question is, how can we utilize nano photonics? I'm gonna just briefly show you the two directions on that which we're working on. One is based on lithium Diabate, and the other is based on even a smaller resonate er's could you? So the work on Nana Photonic lithium naive. It was started in collaboration with Harvard Marko Loncar, and also might affair at Stanford. And, uh, we could show that you can do the periodic polling in the phenomenon of it and get all sorts of very highly nonlinear processes happening in this net. Photonic periodically polls if, um Diabate. And now we're working on building. Opio was based on that kind of photonic the film Diabate. And these air some some examples of the devices that we have been building in the past few months, which I'm not gonna tell you more about. But the O. P. O. S. And the Opio Networks are in the works. And that's not the only way of making large networks. Um, but also I want to point out that The reason that these Nana photonic goblins are actually exciting is not just because you can make a large networks and it can make him compact in a in a small footprint. They also provide some opportunities in terms of the operation regime. On one of them is about making cat states and Opio, which is, can we have the quantum superposition of the zero pie states that I talked about and the Net a photonic within? I've It provides some opportunities to actually get closer to that regime because of the spatial temporal confinement that you can get in these wave guides. So we're doing some theory on that. We're confident that the type of non linearity two losses that it can get with these platforms are actually much higher than what you can get with other platform their existing platforms and to go even smaller. We have been asking the question off. What is the smallest possible Opio that you can make? Then you can think about really wavelength scale type, resonate er's and adding the chi to non linearity and see how and when you can get the Opio to operate. And recently, in collaboration with us see, we have been actually USC and Creole. We have demonstrated that you can use nano lasers and get some spin Hamilton and implementations on those networks. So if you can build the a P. O s, we know that there is a path for implementing Opio Networks on on such a nano scale. So we have looked at these calculations and we try to estimate the threshold of a pos. Let's say for me resonator and it turns out that it can actually be even lower than the type of bulk Pip Llano Pos that we have been building in the past 50 years or so. So we're working on the experiments and we're hoping that we can actually make even larger and larger scale Opio networks. So let me summarize the talk I told you about the opium networks and our work that has been going on on icing machines and the measurement feedback. And I told you about the ongoing work on the all optical implementations both on the linear side and also on the nonlinear behaviors. And I also told you a little bit about the efforts on miniaturization and going to the to the Nano scale. So with that, I would like Thio >>three from the University of Tokyo. Before I thought that would like to thank you showing all the stuff of entity for the invitation and the organization of this online meeting and also would like to say that it has been very exciting to see the growth of this new film lab. And I'm happy to share with you today of some of the recent works that have been done either by me or by character of Hong Kong. Honest Group indicates the title of my talk is a neuro more fic in silica simulator for the communities in machine. And here is the outline I would like to make the case that the simulation in digital Tektronix of the CME can be useful for the better understanding or improving its function principles by new job introducing some ideas from neural networks. This is what I will discuss in the first part and then it will show some proof of concept of the game and performance that can be obtained using dissimulation in the second part and the protection of the performance that can be achieved using a very large chaos simulator in the third part and finally talk about future plans. So first, let me start by comparing recently proposed izing machines using this table there is elected from recent natural tronics paper from the village Park hard people, and this comparison shows that there's always a trade off between energy efficiency, speed and scalability that depends on the physical implementation. So in red, here are the limitation of each of the servers hardware on, interestingly, the F p G, a based systems such as a producer, digital, another uh Toshiba beautification machine or a recently proposed restricted Bozeman machine, FPD A by a group in Berkeley. They offer a good compromise between speed and scalability. And this is why, despite the unique advantage that some of these older hardware have trust as the currency proposition in Fox, CBS or the energy efficiency off memory Sisters uh P. J. O are still an attractive platform for building large organizing machines in the near future. The reason for the good performance of Refugee A is not so much that they operate at the high frequency. No, there are particular in use, efficient, but rather that the physical wiring off its elements can be reconfigured in a way that limits the funding human bottleneck, larger, funny and phenols and the long propagation video information within the system. In this respect, the LPGA is They are interesting from the perspective off the physics off complex systems, but then the physics of the actions on the photos. So to put the performance of these various hardware and perspective, we can look at the competition of bringing the brain the brain complete, using billions of neurons using only 20 watts of power and operates. It's a very theoretically slow, if we can see and so this impressive characteristic, they motivate us to try to investigate. What kind of new inspired principles be useful for designing better izing machines? The idea of this research project in the future collaboration it's to temporary alleviates the limitations that are intrinsic to the realization of an optical cortex in machine shown in the top panel here. By designing a large care simulator in silicone in the bottom here that can be used for digesting the better organization principles of the CIA and this talk, I will talk about three neuro inspired principles that are the symmetry of connections, neural dynamics orphan chaotic because of symmetry, is interconnectivity the infrastructure? No. Next talks are not composed of the reputation of always the same types of non environments of the neurons, but there is a local structure that is repeated. So here's the schematic of the micro column in the cortex. And lastly, the Iraqi co organization of connectivity connectivity is organizing a tree structure in the brain. So here you see a representation of the Iraqi and organization of the monkey cerebral cortex. So how can these principles we used to improve the performance of the icing machines? And it's in sequence stimulation. So, first about the two of principles of the estimate Trian Rico structure. We know that the classical approximation of the car testing machine, which is the ground toe, the rate based on your networks. So in the case of the icing machines, uh, the okay, Scott approximation can be obtained using the trump active in your position, for example, so the times of both of the system they are, they can be described by the following ordinary differential equations on in which, in case of see, I am the X, I represent the in phase component of one GOP Oh, Theo f represents the monitor optical parts, the district optical Parametric amplification and some of the good I JoJo extra represent the coupling, which is done in the case of the measure of feedback coupling cm using oh, more than detection and refugee A and then injection off the cooking time and eso this dynamics in both cases of CNN in your networks, they can be written as the grand set of a potential function V, and this written here, and this potential functionally includes the rising Maccagnan. So this is why it's natural to use this type of, uh, dynamics to solve the icing problem in which the Omega I J or the eyes in coping and the H is the extension of the icing and attorney in India and expect so. Not that this potential function can only be defined if the Omega I j. R. A. Symmetric. So the well known problem of this approach is that this potential function V that we obtain is very non convicts at low temperature, and also one strategy is to gradually deformed this landscape, using so many in process. But there is no theorem. Unfortunately, that granted conventions to the global minimum of There's even Tony and using this approach. And so this is why we propose, uh, to introduce a macro structures of the system where one analog spin or one D O. P. O is replaced by a pair off one another spin and one error, according viable. And the addition of this chemical structure introduces a symmetry in the system, which in terms induces chaotic dynamics, a chaotic search rather than a learning process for searching for the ground state of the icing. Every 20 within this massacre structure the role of the er variable eyes to control the amplitude off the analog spins toe force. The amplitude of the expense toe become equal to certain target amplitude a uh and, uh, and this is done by modulating the strength off the icing complaints or see the the error variable E I multiply the icing complaint here in the dynamics off air d o p. O. On then the dynamics. The whole dynamics described by this coupled equations because the e I do not necessarily take away the same value for the different. I thesis introduces a symmetry in the system, which in turn creates security dynamics, which I'm sure here for solving certain current size off, um, escape problem, Uh, in which the X I are shown here and the i r from here and the value of the icing energy showing the bottom plots. You see this Celtics search that visit various local minima of the as Newtonian and eventually finds the global minimum? Um, it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing evertonians so that we're gonna do not get stuck in any of them. On more over the other types of attractors I can eventually appear, such as limits I contractors, Okot contractors. They can also be destabilized using the motivation of the target and Batuta. And so we have proposed in the past two different moderation of the target amateur. The first one is a modulation that ensure the uh 100 reproduction rate of the system to become positive on this forbids the creation off any nontrivial tractors. And but in this work, I will talk about another moderation or arrested moderation which is given here. That works, uh, as well as this first uh, moderation, but is easy to be implemented on refugee. So this couple of the question that represent becoming the stimulation of the cortex in machine with some error correction they can be implemented especially efficiently on an F B. G. And here I show the time that it takes to simulate three system and also in red. You see, at the time that it takes to simulate the X I term the EI term, the dot product and the rising Hamiltonian for a system with 500 spins and Iraq Spain's equivalent to 500 g. O. P. S. So >>in >>f b d a. The nonlinear dynamics which, according to the digital optical Parametric amplification that the Opa off the CME can be computed in only 13 clock cycles at 300 yards. So which corresponds to about 0.1 microseconds. And this is Toby, uh, compared to what can be achieved in the measurements back O C. M. In which, if we want to get 500 timer chip Xia Pios with the one she got repetition rate through the obstacle nine narrative. Uh, then way would require 0.5 microseconds toe do this so the submission in F B J can be at least as fast as ah one g repression. Uh, replicate pulsed laser CIA Um, then the DOT product that appears in this differential equation can be completed in 43 clock cycles. That's to say, one microseconds at 15 years. So I pieced for pouring sizes that are larger than 500 speeds. The dot product becomes clearly the bottleneck, and this can be seen by looking at the the skating off the time the numbers of clock cycles a text to compute either the non in your optical parts or the dog products, respect to the problem size. And And if we had infinite amount of resources and PGA to simulate the dynamics, then the non illogical post can could be done in the old one. On the mattress Vector product could be done in the low carrot off, located off scales as a look at it off and and while the guide off end. Because computing the dot product involves assuming all the terms in the product, which is done by a nephew, GE by another tree, which heights scarce logarithmic any with the size of the system. But This is in the case if we had an infinite amount of resources on the LPGA food, but for dealing for larger problems off more than 100 spins. Usually we need to decompose the metrics into ah, smaller blocks with the block side that are not you here. And then the scaling becomes funny, non inner parts linear in the end, over you and for the products in the end of EU square eso typically for low NF pdf cheap PGA you the block size off this matrix is typically about 100. So clearly way want to make you as large as possible in order to maintain this scanning in a log event for the numbers of clock cycles needed to compute the product rather than this and square that occurs if we decompose the metrics into smaller blocks. But the difficulty in, uh, having this larger blocks eyes that having another tree very large Haider tree introduces a large finding and finance and long distance start a path within the refugee. So the solution to get higher performance for a simulator of the contest in machine eyes to get rid of this bottleneck for the dot product by increasing the size of this at the tree. And this can be done by organizing your critique the electrical components within the LPGA in order which is shown here in this, uh, right panel here in order to minimize the finding finance of the system and to minimize the long distance that a path in the in the fpt So I'm not going to the details of how this is implemented LPGA. But just to give you a idea off why the Iraqi Yahiko organization off the system becomes the extremely important toe get good performance for similar organizing machine. So instead of instead of getting into the details of the mpg implementation, I would like to give some few benchmark results off this simulator, uh, off the that that was used as a proof of concept for this idea which is can be found in this archive paper here and here. I should results for solving escape problems. Free connected person, randomly person minus one spring last problems and we sure, as we use as a metric the numbers of the mattress Victor products since it's the bottleneck of the computation, uh, to get the optimal solution of this escape problem with the Nina successful BT against the problem size here and and in red here, this propose FDJ implementation and in ah blue is the numbers of retrospective product that are necessary for the C. I am without error correction to solve this escape programs and in green here for noisy means in an evening which is, uh, behavior with similar to the Cartesian mission. Uh, and so clearly you see that the scaring off the numbers of matrix vector product necessary to solve this problem scales with a better exponents than this other approaches. So So So that's interesting feature of the system and next we can see what is the real time to solution to solve this SK instances eso in the last six years, the time institution in seconds to find a grand state of risk. Instances remain answers probability for different state of the art hardware. So in red is the F B g. A presentation proposing this paper and then the other curve represent Ah, brick a local search in in orange and silver lining in purple, for example. And so you see that the scaring off this purpose simulator is is rather good, and that for larger plant sizes we can get orders of magnitude faster than the state of the art approaches. Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FPD implementation would be faster than risk. Other recently proposed izing machine, such as the hope you know, natural complimented on memories distance that is very fast for small problem size in blue here, which is very fast for small problem size. But which scanning is not good on the same thing for the restricted Bosman machine. Implementing a PGA proposed by some group in Broken Recently Again, which is very fast for small parliament sizes but which canning is bad so that a dis worse than the proposed approach so that we can expect that for programs size is larger than 1000 spins. The proposed, of course, would be the faster one. Let me jump toe this other slide and another confirmation that the scheme scales well that you can find the maximum cut values off benchmark sets. The G sets better candidates that have been previously found by any other algorithms, so they are the best known could values to best of our knowledge. And, um or so which is shown in this paper table here in particular, the instances, uh, 14 and 15 of this G set can be We can find better converse than previously known, and we can find this can vary is 100 times faster than the state of the art algorithm and CP to do this which is a very common Kasich. It s not that getting this a good result on the G sets, they do not require ah, particular hard tuning of the parameters. So the tuning issuing here is very simple. It it just depends on the degree off connectivity within each graph. And so this good results on the set indicate that the proposed approach would be a good not only at solving escape problems in this problems, but all the types off graph sizing problems on Mexican province in communities. So given that the performance off the design depends on the height of this other tree, we can try to maximize the height of this other tree on a large F p g a onda and carefully routing the components within the P G A and and we can draw some projections of what type of performance we can achieve in the near future based on the, uh, implementation that we are currently working. So here you see projection for the time to solution way, then next property for solving this escape programs respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital. And, you know, 42 is shown in the green here, the green line without that's and, uh and we should two different, uh, hypothesis for this productions either that the time to solution scales as exponential off n or that the time of social skills as expression of square root off. So it seems, according to the data, that time solution scares more as an expression of square root of and also we can be sure on this and this production show that we probably can solve prime escape problem of science 2000 spins, uh, to find the rial ground state of this problem with 99 success ability in about 10 seconds, which is much faster than all the other proposed approaches. So one of the future plans for this current is in machine simulator. So the first thing is that we would like to make dissimulation closer to the rial, uh, GOP oh, optical system in particular for a first step to get closer to the system of a measurement back. See, I am. And to do this what is, uh, simulate Herbal on the p a is this quantum, uh, condoms Goshen model that is proposed described in this paper and proposed by people in the in the Entity group. And so the idea of this model is that instead of having the very simple or these and have shown previously, it includes paired all these that take into account on me the mean off the awesome leverage off the, uh, European face component, but also their violence s so that we can take into account more quantum effects off the g o p. O, such as the squeezing. And then we plan toe, make the simulator open access for the members to run their instances on the system. There will be a first version in September that will be just based on the simple common line access for the simulator and in which will have just a classic or approximation of the system. We don't know Sturm, binary weights and museum in term, but then will propose a second version that would extend the current arising machine to Iraq off F p g. A, in which we will add the more refined models truncated, ignoring the bottom Goshen model they just talked about on the support in which he valued waits for the rising problems and support the cement. So we will announce later when this is available and and far right is working >>hard comes from Universal down today in physics department, and I'd like to thank the organizers for their kind invitation to participate in this very interesting and promising workshop. Also like to say that I look forward to collaborations with with a file lab and Yoshi and collaborators on the topics of this world. So today I'll briefly talk about our attempt to understand the fundamental limits off another continues time computing, at least from the point off you off bullion satisfy ability, problem solving, using ordinary differential equations. But I think the issues that we raise, um, during this occasion actually apply to other other approaches on a log approaches as well and into other problems as well. I think everyone here knows what Dorien satisfy ability. Problems are, um, you have boolean variables. You have em clauses. Each of disjunction of collaterals literally is a variable, or it's, uh, negation. And the goal is to find an assignment to the variable, such that order clauses are true. This is a decision type problem from the MP class, which means you can checking polynomial time for satisfy ability off any assignment. And the three set is empty, complete with K three a larger, which means an efficient trees. That's over, uh, implies an efficient source for all the problems in the empty class, because all the problems in the empty class can be reduced in Polian on real time to reset. As a matter of fact, you can reduce the NP complete problems into each other. You can go from three set to set backing or two maximum dependent set, which is a set packing in graph theoretic notions or terms toe the icing graphs. A problem decision version. This is useful, and you're comparing different approaches, working on different kinds of problems when not all the closest can be satisfied. You're looking at the accusation version offset, uh called Max Set. And the goal here is to find assignment that satisfies the maximum number of clauses. And this is from the NPR class. In terms of applications. If we had inefficient sets over or np complete problems over, it was literally, positively influenced. Thousands off problems and applications in industry and and science. I'm not going to read this, but this this, of course, gives a strong motivation toe work on this kind of problems. Now our approach to set solving involves embedding the problem in a continuous space, and you use all the east to do that. So instead of working zeros and ones, we work with minus one across once, and we allow the corresponding variables toe change continuously between the two bounds. We formulate the problem with the help of a close metrics. If if a if a close, uh, does not contain a variable or its negation. The corresponding matrix element is zero. If it contains the variable in positive, for which one contains the variable in a gated for Mitt's negative one, and then we use this to formulate this products caused quote, close violation functions one for every clause, Uh, which really, continuously between zero and one. And they're zero if and only if the clause itself is true. Uh, then we form the define in order to define a dynamic such dynamics in this and dimensional hyper cube where the search happens and if they exist, solutions. They're sitting in some of the corners of this hyper cube. So we define this, uh, energy potential or landscape function shown here in a way that this is zero if and only if all the clauses all the kmc zero or the clauses off satisfied keeping these auxiliary variables a EMS always positive. And therefore, what you do here is a dynamics that is a essentially ingredient descend on this potential energy landscape. If you were to keep all the M's constant that it would get stuck in some local minimum. However, what we do here is we couple it with the dynamics we cooperated the clothes violation functions as shown here. And if he didn't have this am here just just the chaos. For example, you have essentially what case you have positive feedback. You have increasing variable. Uh, but in that case, you still get stuck would still behave will still find. So she is better than the constant version but still would get stuck only when you put here this a m which makes the dynamics in in this variable exponential like uh, only then it keeps searching until he finds a solution on deer is a reason for that. I'm not going toe talk about here, but essentially boils down toe performing a Grady and descend on a globally time barren landscape. And this is what works. Now I'm gonna talk about good or bad and maybe the ugly. Uh, this is, uh, this is What's good is that it's a hyperbolic dynamical system, which means that if you take any domain in the search space that doesn't have a solution in it or any socially than the number of trajectories in it decays exponentially quickly. And the decay rate is a characteristic in variant characteristic off the dynamics itself. Dynamical systems called the escape right the inverse off that is the time scale in which you find solutions by this by this dynamical system, and you can see here some song trajectories that are Kelty because it's it's no linear, but it's transient, chaotic. Give their sources, of course, because eventually knowledge to the solution. Now, in terms of performance here, what you show for a bunch off, um, constraint densities defined by M overran the ratio between closes toe variables for random, said Problems is random. Chris had problems, and they as its function off n And we look at money toward the wartime, the wall clock time and it behaves quite value behaves Azat party nominally until you actually he to reach the set on set transition where the hardest problems are found. But what's more interesting is if you monitor the continuous time t the performance in terms off the A narrow, continuous Time t because that seems to be a polynomial. And the way we show that is, we consider, uh, random case that random three set for a fixed constraint density Onda. We hear what you show here. Is that the right of the trash hold that it's really hard and, uh, the money through the fraction of problems that we have not been able to solve it. We select thousands of problems at that constraint ratio and resolve them without algorithm, and we monitor the fractional problems that have not yet been solved by continuous 90. And this, as you see these decays exponentially different. Educate rates for different system sizes, and in this spot shows that is dedicated behaves polynomial, or actually as a power law. So if you combine these two, you find that the time needed to solve all problems except maybe appear traction off them scales foreign or merely with the problem size. So you have paranormal, continuous time complexity. And this is also true for other types of very hard constraints and sexual problems such as exact cover, because you can always transform them into three set as we discussed before, Ramsey coloring and and on these problems, even algorithms like survey propagation will will fail. But this doesn't mean that P equals NP because what you have first of all, if you were toe implement these equations in a device whose behavior is described by these, uh, the keys. Then, of course, T the continue style variable becomes a physical work off. Time on that will be polynomial is scaling, but you have another other variables. Oxidative variables, which structured in an exponential manner. So if they represent currents or voltages in your realization and it would be an exponential cost Al Qaeda. But this is some kind of trade between time and energy, while I know how toe generate energy or I don't know how to generate time. But I know how to generate energy so it could use for it. But there's other issues as well, especially if you're trying toe do this son and digital machine but also happens. Problems happen appear. Other problems appear on in physical devices as well as we discuss later. So if you implement this in GPU, you can. Then you can get in order off to magnitude. Speed up. And you can also modify this to solve Max sad problems. Uh, quite efficiently. You are competitive with the best heuristic solvers. This is a weather problems. In 2016 Max set competition eso so this this is this is definitely this seems like a good approach, but there's off course interesting limitations, I would say interesting, because it kind of makes you think about what it means and how you can exploit this thes observations in understanding better on a low continues time complexity. If you monitored the discrete number the number of discrete steps. Don't buy the room, Dakota integrator. When you solve this on a digital machine, you're using some kind of integrator. Um and you're using the same approach. But now you measure the number off problems you haven't sold by given number of this kid, uh, steps taken by the integrator. You find out you have exponential, discrete time, complexity and, of course, thistles. A problem. And if you look closely, what happens even though the analog mathematical trajectory, that's the record here. If you monitor what happens in discrete time, uh, the integrator frustrates very little. So this is like, you know, third or for the disposition, but fluctuates like crazy. So it really is like the intervention frees us out. And this is because of the phenomenon of stiffness that are I'll talk a little bit a more about little bit layer eso. >>You know, it might look >>like an integration issue on digital machines that you could improve and could definitely improve. But actually issues bigger than that. It's It's deeper than that, because on a digital machine there is no time energy conversion. So the outside variables are efficiently representing a digital machine. So there's no exponential fluctuating current of wattage in your computer when you do this. Eso If it is not equal NP then the exponential time, complexity or exponential costs complexity has to hit you somewhere. And this is how um, but, you know, one would be tempted to think maybe this wouldn't be an issue in a analog device, and to some extent is true on our devices can be ordered to maintain faster, but they also suffer from their own problems because he not gonna be affect. That classes soldiers as well. So, indeed, if you look at other systems like Mirandizing machine measurement feedback, probably talk on the grass or selected networks. They're all hinge on some kind off our ability to control your variables in arbitrary, high precision and a certain networks you want toe read out across frequencies in case off CM's. You required identical and program because which is hard to keep, and they kind of fluctuate away from one another, shift away from one another. And if you control that, of course that you can control the performance. So actually one can ask if whether or not this is a universal bottleneck and it seems so aside, I will argue next. Um, we can recall a fundamental result by by showing harder in reaction Target from 1978. Who says that it's a purely computer science proof that if you are able toe, compute the addition multiplication division off riel variables with infinite precision, then you could solve any complete problems in polynomial time. It doesn't actually proposals all where he just chose mathematically that this would be the case. Now, of course, in Real warned, you have also precision. So the next question is, how does that affect the competition about problems? This is what you're after. Lots of precision means information also, or entropy production. Eso what you're really looking at the relationship between hardness and cost of computing off a problem. Uh, and according to Sean Hagar, there's this left branch which in principle could be polynomial time. But the question whether or not this is achievable that is not achievable, but something more cheerful. That's on the right hand side. There's always going to be some information loss, so mental degeneration that could keep you away from possibly from point normal time. So this is what we like to understand, and this information laws the source off. This is not just always I will argue, uh, in any physical system, but it's also off algorithm nature, so that is a questionable area or approach. But China gets results. Security theoretical. No, actual solar is proposed. So we can ask, you know, just theoretically get out off. Curiosity would in principle be such soldiers because it is not proposing a soldier with such properties. In principle, if if you want to look mathematically precisely what the solar does would have the right properties on, I argue. Yes, I don't have a mathematical proof, but I have some arguments that that would be the case. And this is the case for actually our city there solver that if you could calculate its trajectory in a loss this way, then it would be, uh, would solve epic complete problems in polynomial continuous time. Now, as a matter of fact, this a bit more difficult question, because time in all these can be re scared however you want. So what? Burns says that you actually have to measure the length of the trajectory, which is a new variant off the dynamical system or property dynamical system, not off its parameters ization. And we did that. So Suba Corral, my student did that first, improving on the stiffness off the problem off the integrations, using implicit solvers and some smart tricks such that you actually are closer to the actual trajectory and using the same approach. You know what fraction off problems you can solve? We did not give the length of the trajectory. You find that it is putting on nearly scaling the problem sites we have putting on your skin complexity. That means that our solar is both Polly length and, as it is, defined it also poorly time analog solver. But if you look at as a discreet algorithm, if you measure the discrete steps on a digital machine, it is an exponential solver. And the reason is because off all these stiffness, every integrator has tow truck it digitizing truncate the equations, and what it has to do is to keep the integration between the so called stability region for for that scheme, and you have to keep this product within a grimace of Jacoby in and the step size read in this region. If you use explicit methods. You want to stay within this region? Uh, but what happens that some off the Eigen values grow fast for Steve problems, and then you're you're forced to reduce that t so the product stays in this bonded domain, which means that now you have to you're forced to take smaller and smaller times, So you're you're freezing out the integration and what I will show you. That's the case. Now you can move to increase its soldiers, which is which is a tree. In this case, you have to make domain is actually on the outside. But what happens in this case is some of the Eigen values of the Jacobean, also, for six systems, start to move to zero. As they're moving to zero, they're going to enter this instability region, so your soul is going to try to keep it out, so it's going to increase the data T. But if you increase that to increase the truncation hours, so you get randomized, uh, in the large search space, so it's it's really not, uh, not going to work out. Now, one can sort off introduce a theory or language to discuss computational and are computational complexity, using the language from dynamical systems theory. But basically I I don't have time to go into this, but you have for heart problems. Security object the chaotic satellite Ouch! In the middle of the search space somewhere, and that dictates how the dynamics happens and variant properties off the dynamics. Of course, off that saddle is what the targets performance and many things, so a new, important measure that we find that it's also helpful in describing thesis. Another complexity is the so called called Makarov, or metric entropy and basically what this does in an intuitive A eyes, uh, to describe the rate at which the uncertainty containing the insignificant digits off a trajectory in the back, the flow towards the significant ones as you lose information because off arrows being, uh grown or are developed in tow. Larger errors in an exponential at an exponential rate because you have positively up north spawning. But this is an in variant property. It's the property of the set of all. This is not how you compute them, and it's really the interesting create off accuracy philosopher dynamical system. A zay said that you have in such a high dimensional that I'm consistent were positive and negatively upon of exponents. Aziz Many The total is the dimension of space and user dimension, the number off unstable manifold dimensions and as Saddam was stable, manifold direction. And there's an interesting and I think, important passion, equality, equality called the passion, equality that connect the information theoretic aspect the rate off information loss with the geometric rate of which trajectory separate minus kappa, which is the escape rate that I already talked about. Now one can actually prove a simple theorems like back off the envelope calculation. The idea here is that you know the rate at which the largest rated, which closely started trajectory separate from one another. So now you can say that, uh, that is fine, as long as my trajectory finds the solution before the projective separate too quickly. In that case, I can have the hope that if I start from some region off the face base, several close early started trajectories, they kind of go into the same solution orphaned and and that's that's That's this upper bound of this limit, and it is really showing that it has to be. It's an exponentially small number. What? It depends on the end dependence off the exponents right here, which combines information loss rate and the social time performance. So these, if this exponents here or that has a large independence or river linear independence, then you then you really have to start, uh, trajectories exponentially closer to one another in orderto end up in the same order. So this is sort off like the direction that you're going in tow, and this formulation is applicable toe all dynamical systems, uh, deterministic dynamical systems. And I think we can We can expand this further because, uh, there is, ah, way off getting the expression for the escaped rate in terms off n the number of variables from cycle expansions that I don't have time to talk about. What? It's kind of like a program that you can try toe pursuit, and this is it. So the conclusions I think of self explanatory I think there is a lot of future in in, uh, in an allo. Continue start computing. Um, they can be efficient by orders of magnitude and digital ones in solving empty heart problems because, first of all, many of the systems you like the phone line and bottleneck. There's parallelism involved, and and you can also have a large spectrum or continues time, time dynamical algorithms than discrete ones. And you know. But we also have to be mindful off. What are the possibility of what are the limits? And 11 open question is very important. Open question is, you know, what are these limits? Is there some kind off no go theory? And that tells you that you can never perform better than this limit or that limit? And I think that's that's the exciting part toe to derive thes thes this levian 10.

>> Thank you for coming to this talk. My name is Amir Safavi-Naeini I'm an Assistant Professor in Applied Physics at Stanford University. And today I'm going to talk about a platform that we've been developing here that allows for quantum and classical information processing using photons and phonons or mechanical motion. So first I'd like to start off, with a picture of the people who did the work. These are graduate students and postdocs in my group. In addition, I want to say that a lot of the work especially on polling of the Lithium niobate was done in collaboration with Martin Fejer's group and in particular Dr.Langrock and Jata Mishra and Marc Jankowski Now our goal is to realize a platform, for quantum coherent information processing, that enables functionality which currently does not exist in other platforms that are available. So in particular we want to have, a very low loss non-linearity that is strong and can be dispersion engineered, to be made broadband. We'd like to make circuits that are programmable and reconfigurable, and that necessitates having efficient modulation and switching. And we'd also really like to have a platform that can leverage some of the advances with superconducting circuits to enable sort of large scale programmable dynamics between many different oscillators on a chip. So, in the next few years what we're really hoping to demonstrate are few photon, optical nonlinear effects by pushing the strength of these non-linearities and reducing the amount of loss. And we also want to demonstrate these coupled, sort of qubit and many oscillators systems. Now the Material system, that we think will enable a lot of these advances is based on lithium niobate, so lithium niobate is a fair electric crystal. It's used very widely in optical components and in acousto optics and then surface acoustic wave devices. It's a fair electric crystal, that has sort of a built-in polarization. And that enables, a lot of effects, which are very useful including the piezoelectric effect, electro- optic effects. And it has a very large K2 optical non-linearity. So it allows for three wave mixing. It also has some effects that are not so great for example, pyroelectricity but because it's very, established material system there's a lot of tricks on how to deal with some of the less attractive parts of it of this material. Now most, Surface Acoustic Wave, or optical devices that you would find are based on kind of bulk lithium niobate crystals that either use surface acoustic waves that propagate on a surface or, you know, bulk waves propagating through a whole crystal, or have a very weak weakly guided low index contrast waveguide that's patterned in the lithium niobate. This was the case until just a little over a decade ago. And this work from ETH Zurich came showing that thin-film lithium niobate can be, bonded and patterned. And Photonic circuits very similar to assigning circuits made from three fives or Silicon can be implemented in this material system. And this really led to a lot of different efforts from different labs. I would say the major breakthrough came, just a few years ago from Marko Loncar, where they demonstrate that high quality factors are possible to realize in this platform. And so they showed resonators with quality factors in the tens of billions corresponding to, line widths of tens of megahertz or losses of, just a few, DB per meter. And so that really changed the picture and you know a little bit after that in collaboration with Martin Fejer's group at Stanford they were able to demonstrate polling and so very large this version engineered nonlinear effects and these types of waveguides. And, and so that showed that, sort of very new types of circuits can be possible on this platform Now our approach is very similar. So we have a thin film of lithium niobate and this time it's on Sapphire instead of oxide or some polymer. and sometimes we put oxide on top. Some Silicon oxide on top, and we can also put electrodes these electrodes can be made out of a superconductor like niobium or aluminum or they can be gold depending on what we're trying to do. The sort of important thing here is that the large index contrast means that, light is guided in a very highly confined waveguide. And it supports bends with small bending radii. And that means we can have resonators that are very small. So the mode volume for the photonic resonators can be very small and as is well known. The interaction rate scale is, one over squared of mode volume. And so we're talking about an enhancement of around six orders of magnitude in the interaction length interaction lengths, over systems using sort of bulk components. And this is in a circuit that's sort of sub millimeter in size and its made on this platform. Now interaction length is important but also quality factor is very important. So when you make these things smaller you don't want to make them much less here. That's, you know, you can look at, for example a second harmonic generation efficiency in these types of resonances and that scales as Q, to the power of three essentially. So you need to achieve, you win a lot by going to low loss circuits. Now loss and non-linearity or sort of material and waveguide properties that we can engineer, but design of these circuits, careful design of these circuits is also very important. For example, you know, because these are highly confined waves and dielectric wave guides they can, you can support several different orders of modes especially if you're working for a broad band light waves that span, you know, an octave. And now when you try to couple light in and out of these structures, you have to be very careful that you're only picking up the polarizations that you care about, and you're not inducing extra loss channels effectively reducing the queue, even though there's no material loss if you're these parasitic coupling, can lead to lower Q. so the design is very important. This plot demonstrates, you know, the types of extrinsic to intrinsic coupling that are needed to achieve very high efficiency SHG, which is unrelated to optical parametric oscillation. And, you know, you, so you sort of have to work in a regime where the extrinsic couplings are much larger than the intrinsic couplings. And this is generally true for any type of quantum operation that you want to do. So just just low material loss itself isn't enough to design is also very important. In terms of where we are, on these three important aspects like getting large G large Q and large cap up. So we've been able to achieve high Q in, in these structures. This is a Q a of a couple million, we've also been able to you can see from a broad transmission spectrum through a grading coupler you can see a very evenly spaced modes showing that we're only coupling to one mode family. And we can see that the depth of the modes is also very large, you know, 90% or more. And that means that our extrinsic coupling in intrinsic coupling is also very large. So we've been able to kind of engineer these devices and to achieve this in terms of the interaction, I won't go over it too much but, you know, in collaboration with Marty Feres group we were able to pull both lithium niobate on insulator and lithium niobate on Sapphire. We'll be able to see a very efficient, sort of high slope proficiency second harmonic generation, you know achieving approaching 5000% per watt centimeters squared for 1560 to 780 conversion. So this is all work in progress. And so for now, I'd like to talk a little bit about the integration of acoustic and mechanical components. So, first of all why would we want to integrate mechanical components? Well, there's lots of cases where, for example you want to have an extremely high extinction switching functionality. That's very difficult to do with electro optics because they need to control the phase, extremely efficiently with extreme precision. You would need very large, long resonators and or large voltages becomes very difficult to achieve you know, 60 DB types of, switching. Mechanical systems. On the other hand, they can have very small mode volumes and can give you 60 DB switching without too many complications. Of course the drawback is that they're slower, but for a lot of applications, that doesn't matter too much. So in terms of being able to make integrate memes, switching and tuning with this platform, here's a device that achieves that so that each of these beams is actuated through the Piezoelectric effect and lithium niobate via this pair of electrodes that we put a voltage across. And when you put a voltage across these have been designed to leverage one of the off diagonal terms in the piezoelectric tensor, which causes bending. And so this bending generates a very large displacement in the center of this beam, in this beam, you might notice is composed of a grading, and this grading effectively generates it's photonic crystal cavity. So it generates a localize optical mode in the center which is very sensitive to these displacements. And what we're able to see in this system is that you know, just a few millivolts so 50 millivolts here shifts the resonance frequency by much more than a line width just a few millivolts is enough to shift by a line width. And so to achieve switching we can also tune this resonance across the full telecom band and these types of devices whether in waveguide resonator form can be extremely useful for sort of phase control in a large scale system, where you might want to have many many face switches on a chip to control phases with, with low loss, because these wave guides are shorter. You have lower loss propagating across them. Now, these interactions are fairly low frequency. When we go to higher frequency, we can use the electro-optic effect. And even the electro-optic effect even though it's very widely used, and well-known on a Photonic circuit like these lithium Niobate for tying circuits has, interesting consequences and device opportunities that don't exist on the bulk devices. So for example, let's look at single sideband modulation. This is what an electro-optic sort of standard electro optics, single sideband modulator looks like you, you take your light, you split into two parts, and then you modulate each of these arms. You modulate them out of phase with an RFC tone that's out of phase. And so now you generate side bands on both and now because they're modulating out of phase when they are recombined and on the output splitter and this mock sender interferometer you end up dropping one of the side bands and then the pump and you end up with a shifted side pan. So that's possible you can do single side band modulation with an electronic device but the caveat is that this is now fundamentally lossy. So, you know, you have generated, this other side band via modulation, and the sideband is simply being lost due to interference. So it's their, It's getting combined, it's getting scattered away because there's no mode that it can get connected to. So actually you know, this is going kind of an efficiency less than 3DB usually much less than 3DB. And that's fine if you just have one of these single sideband modulators because you can always amplify, you can send more power but if you're talking about a system and you have many of these and you can't put amplifiers everywhere then, or you're working with quantum information where loss is particularly bad. This is not an option. Now, when you use resonators, you have another option. So here's a device that tries to demonstrate this. This is two resonators that are brought into the near-field of each other. So they're coupled with each other over here where they're, which causes a splitting. And now when we tune the DC voltage was tuned one of these resonators by sort of changing the effective half lengths And one of these resonators tunes, the frequency, we can see an We should see an anti crossing between the two modes and at the center of this splitting this is versus voltage, a splitting at the center at this voltage, let's say here it's around 15 volts. We can see two residences two dips, when we probed the line field going through. And now if we send in the pump resonant, with one of these, and we modulate at this difference frequency we generate this red side band but we actually don't generate the blue side band because there's no optical density of state. So the, so because there's this other side may has just not generated. This system is now much more efficient. In fact, so in Marco Loncar has give they've demonstrated. You can get a hundred percent conversion. And we've also demonstrated this in a similar experiment showing that you can get very large sideband suppression. So, you know more than 30 DB suppression of the side bands with respect to the sideband that you care about It's also interesting that these interactions now preserve quantum coherence. And this is one path to creating links between superconducting microwave systems and optical components. Because now the microwave signal that's scattered here preserves its coherence. So we've also been able to do acoustic optic interactions at these high frequencies. This is a, this is an acoustic optic modulator that operates at a few gigahertz. Basically you generate electric field here which generates a propagating wave inside this transducer made out of lithium niobate. These are aluminum electrodes on top. The phonons are focused down into a small phononic waveguides that guides mechanical waves. And then these are brought into this crystal area where the sound and the Mo and the light are both convert confined to wavelength skill mode volume and they interact very strongly with each other. And the strong interaction leads to very efficient, effective electro-optic modulation. So here we've been able to see, with just a few microwatts of power, many, many side bands being generated. So this is a fact that they like tropic much later where the VPI is, a few thousands of a volt instead of, you know, several volts, which is sort of the off the shelf, electro-optic modulator that you would find. And importantly, we've been able to combine these, photonic and phononic circuits into the same platform. So this is a lithium niobate on same Lithium niobate on Sapphire platform. This is an acoustic transducer that generates mechanical waves that propagate in this lithium niobate waveguide. You can see them here and we can make phononic circuits now. so this is a ring resonate. It's a ring resonator for phonons. So we send sound waves through. And when it's resonance, when its frequency hits the ring residences, we see peaks. and this is, this is cheeks in the drop port coming out. And what's really nice about this platform is that we actually don't need to unlike unlike many memes platforms where you have to have released steps that are usually not compatible with, you know other devices here, there's no release steps. So the phonons are guided in that thin lithium niobate layer. The high Q of these mechanical modes shows that these mechanical resonances can be very coherent oscillators. And so we've also worked towards integrating these with very non-linear microwave circuits to create strongly interacting phonons and phonon circuits. So this is a example of an experiment we did over a year ago, where we have sort of a superconducting Qubit circuit with mechanical resonances made out of lithium niobate shunting the Qubit capacitor to ground. So now vibrations of this mechanical oscillator generate a voltage across these electrodes that couples to the Qubits voltage. And so now you have an interaction between this qubit and the mechanical oscillator, and we can see that in the spectrum of the qubit as we tune it across the frequency band. And we see splittings every time the qubit frequency approaches the mechanical resonance frequency. And infact this coupling is so large, that we were able to observe for the first time, the phonon spectrum. So we can detune this qubit away from the mechanical resonance. And now you have a dispersive shift on the qubit which is proportional to the number of phonons. And because number of photons is quantized. We can actually see, the different phonon levels in the qubit spectrum. Moving forward, we've been trying to, also understand what the sources of loss are in the system. And we've been able to do this by demonstrating by fabricating very large rays in these mechanical oscillators and looking at things like, their quality factor versus frequency. This is an example of a measurement that shows a jump in the quality factor when we enter the frequency band where we expect our phononic band gap for this period, periodic material is this jump you know, in principle,if loss were only due to clamping only due to acoustic waves leaking out in these out of these ends, then this change in quality factor quality factor should go to essentially infinite or should be ex exponential losses should be exponentially suppress with the length So these, but it's not. And that means we're actually limited by other loss channels. And we've been able to determine that these are two level systems and the lithium niobate by looking at the temperature dependence of these losses and seeing that they fit very well sort of standard models that exist for the effects of two level systems on microwave and mechanical resonances. We've also started experimenting with different materials. In fact, we've been able to see that, for example, going to lithium niobate, that's dope with magnesium oxide changes or reduces significantly the effect of the two level systems. And this is a really exciting direction of research that we're pursuing. So we're understanding these materials. So with that, I'd like to thank the sponsors. NTTResearch, of course, a lot of this work was funded by DARPA, ONR, RAO, DOE very generous funding from David and Lucile Packard foundation and others that are shown here. So thank you.

>>Good morning. Good afternoon. Good evening, everyone. I should thank Entity Research and the Oshie for putting together this program and also the opportunity to speak here. My name is Al Gore ism or Andy and I'm from Caltech. And today I'm going to tell you about the work that we have been doing on networks off optical parametric oscillators and how we have been using them for icing machines and how we're pushing them toward Cornum. Photonics should acknowledge my team at Caltech, which is now eight graduate students and five researcher and postdocs as well as collaborators from all over the world, including entity research and also the funding from different places, including entity. So this talk is primarily about networks of resonate er's and these networks are everywhere from nature. For instance, the brain, which is a network of oscillators all the way to optics and photonics and some of the biggest examples or meta materials, which is an array of small resonate er's. And we're recently the field of technological photonics, which is trying thio implement a lot of the technological behaviors of models in the condensed matter, physics in photonics. And if you want to extend it even further. Some of the implementations off quantum computing are technically networks of quantum oscillators. So we started thinking about these things in the context of icing machines, which is based on the icing problem, which is based on the icing model, which is the simple summation over the spins and spins can be their upward down, and the couplings is given by the G I J. And the icing problem is, if you know J I J. What is the spin configuration that gives you the ground state? And this problem is shown to be an MP high problem. So it's computational e important because it's a representative of the MP problems on NPR. Problems are important because first, their heart in standard computers, if you use a brute force algorithm and they're everywhere on the application side. That's why there is this demand for making a machine that can target these problems and hopefully it can provide some meaningful computational benefit compared to the standard digital computers. So I've been building these icing machines based on this building block, which is a degenerate optical parametric oscillator on what it is is resonator with non linearity in it and we pump these resonate er's and we generate the signal at half the frequency of the pump. One vote on a pump splits into two identical photons of signal, and they have some very interesting phase of frequency locking behaviors. And if you look at the phase locking behavior, you realize that you can actually have two possible face states as the escalation result of these Opio, which are off by pie, and that's one of the important characteristics of them. So I want to emphasize >>a little more on that, and I have this mechanical analogy which are basically two simple pendulum. But there are parametric oscillators because I'm going to modulate the parameter of them in this video, which is the length of the strength on by that modulation, which is that will make a pump. I'm gonna make a muscular. That'll make a signal, which is half the frequency of the pump. >>And I have two of them to show you that they can acquire these face states so they're still face their frequency lock to the pump. But it can also lead in either the zero pie face state on. The idea is to use this binary phase to represent the binary icing spin. So each Opio is going to represent spin, which can be >>either is your pie or up or down, >>and to implement the network of these resonate er's. We use the time off blood scheme, and the idea is that we put impulses in the cavity, these pulses air separated by the repetition period that you put in or t R. And you can think about these pulses in one resonator, xaz and temporarily separated synthetic resonate Er's If you want a couple of these resonator is to each other, and now you can introduce these delays, each of which is a multiple of TR. If you look at the shortest delay it couples resonator wanted to 2 to 3 and so on. If you look at the second delay, which is two times a rotation period, the couple's 123 and so on. If you have any minus one delay lines, then you can have any potential couplings among these synthetic resonate er's. And if I can introduce these modulators in those delay lines so that I can strength, I can control the strength and the phase of these couplings at the right time. Then I can >>have a program. We'll all toe all connected network in this time off like scheme. >>And the whole physical size of the system scales linearly with the number of pulses. So the idea of opium based icing machine is didn't having these o pos. Each of them can be either zero pie, and I can arbitrarily connect them to each other. And then I start with programming this machine to a given icing problem by just setting the couplings and setting the controllers in each of those delight lines. So now I have a network which represents an icing problem thin the icing problem maps to finding the face state that satisfy maximum number of coupling constraints. And the way it happens is that the icing Hamiltonian maps to the linear loss of the network. And if I start adding gain by just putting pump into the network, then the OPI ohs are expected to oscillating the lowest, lowest lost state. And, uh and we have been doing these in the past, uh, six or seven years and I'm just going to quickly show you the transition, especially what happened in the first implementation which was using a free space optical system and then the guided wave implementation in 2016 and the measurement feedback idea which led to increasing the size and doing actual computation with these machines. So I just want to make this distinction here that, um the first implementation was on our optical interaction. We also had an unequal 16 implementation and then we transition to this measurement feedback idea, which I'll tell you quickly what it iss on. There's still a lot of ongoing work, especially on the entity side, to make larger machines using the measurement feedback. But I'm gonna mostly focused on the all optical networks and how we're using all optical networks to go beyond simulation of icing. Hamiltonian is both in the linear and >>nonlinear side and also how we're working on miniaturization of these Opio networks. So >>the first experiment, which was the four Opium machine it was a free space implementation and this is the actual picture of the machine and we implemented a small and it calls for Mexico problem on the machine. So one problem for one experiment and we ran the machine 1000 times, we looked at the state and we always saw it oscillate in one of these, um, ground states of the icing laboratoria. Yeah, so then the measurement feedback idea was to replace those couplings and the controller with the simulator. So we basically simulated all those coherent interactions on on FB g A. And we replicated the coherent pulse with respect to all those measurements. And then we injected it back into the cavity and on the near to you still remain. So it still is a non. They're dynamical system, but the linear side is all simulated. So there are lots of questions about if this system is preserving important information or not, or if it's gonna behave better Computational wars. And that's still ah, lot of ongoing studies. But nevertheless, the reason that this implementation was very interesting is that you don't need the end minus one delight lines so you can just use one, and you can implement a large machine, and then you can run several thousands of problems in the machine, and then you can compare the performance from the computational perspective. Looks so I'm gonna split this idea of opium based icing machine into two parts One is the linear part, which is if you take out the non linearity out of the resonator and just think about the connections. You can think about this as a simple matrix multiplication scheme, and that's basically >>what gives you the icing Hamiltonian model A. So the optical loss of this network corresponds to the icing Hamiltonian. >>And if I just want to show you the example of the n equals for experiment on all those face states and the history Graham that we saw, you can actually calculate the laws of each of those states because all those interferences in the beam splitters and the delay lines are going to give you a different losses. And then you will see that ground states corresponds to the lowest laws of the actual optical network. If you add the non linearity, the simple way of thinking about what the non linearity does is that it provides to gain, and then you start bringing up the gain so that it hits the loss. Then you go through the game saturation or the threshold which is going to give you this phase bifurcation. >>So you go either to zero the pie face state, and the expectation is that this the network oscillates in the lowest possible state, the lowest possible loss state. >>There are some challenges associated with this intensity Durban face transition, which I'm going to briefly talk about. I'm also going to tell you about other types of non their dynamics that we're looking at on the non air side of these networks. So if you just think about the linear network, we're actually interested in looking at some technological behaviors in these networks. And the difference between looking at the technological behaviors and the icing uh, machine is that now, First of all, we're looking at the type of Hamilton Ian's that are a little different than the icing Hamilton. And one of the biggest difference is is that most of these technological Hamilton Ian's that require breaking the time reversal symmetry, meaning that you go from one spin to on the one side to another side and you get one phase. And if you go back where you get a different phase, and the other thing is that we're not just interested in finding the ground state, we're actually now interesting and looking at all sorts of States and looking at the dynamics and the behaviors of all these states in the network. So we started with the simplest implementation, of course, which is a one d chain of thes resonate er's which corresponds to a so called ssh model. In the technological work, we get the similar energy to los mapping. And now we can actually look at the band structure on. This is an actual measurement >>that we get with this associate model and you see how it reasonably how how? Well, it actually follows the prediction and the theory. >>One of the interesting things about the time multiplexing implementation is that now you have the flexibility of changing the network as we were running the machine. And that's something unique about this time multiplex implementation so that we can actually look at the dynamics. And one example >>that we have looked at is we can actually go to the transition off going from top a logical to the to the standard nontrivial. I'm sorry to the trivial behavior of the network. >>You can then look at the edge states and you can also see the trivial and states and the technological at states actually showing up in this network. We have just recently implement on a two D, >>uh, network with Harper Hofstadter model when you don't have the results here. But we're one of the other important characteristic of time multiplexing is that you can go to higher and higher dimensions and keeping that flexibility and dynamics. And we can also think about adding non linearity both in a classical and quantum regimes, which is going to give us a lot of exotic oh, classical and quantum, non innate behaviors in these networks. >>So I told you about the linear side. Mostly let me just switch gears and talk about the nonlinear side of the network. And the biggest thing that I talked about so far in the icing machine is this phase transition, that threshold. So the low threshold we have squeezed state in these Oh, pios, if you increase the pump, we go through this intensity driven phase transition and then we got the face stays above threshold. And this is basically the mechanism off the computation in these O pos, which is through this phase transition below to above threshold. So one of the characteristics of this phase transition is that below threshold, you expect to see quantum states above threshold. You expect to see more classical states or coherent states, and that's basically corresponding to the intensity off the driving pump. So it's really hard to imagine that it can go above threshold. Or you can have this friends transition happen in the all in the quantum regime. And there are also some challenges associated with the intensity homogeneity off the network. Which, for example, is if one Opio starts oscillating and then its intensity goes really high. Then it's going to ruin this collective decision making off the network because of the intensity driven face transition nature. So So the question is, can we look at other phase transitions? Can we utilize them for both computing? And also, can we bring them to the quantum regime on? I'm going to specifically talk about the face transition in the spectral domain, which is the transition from the so called degenerate regime, which is what I mostly talked about to the non degenerate regime, which happens by just tuning the phase of the cavity. And what is interesting is that this phase transition corresponds to a distinct phase noise, behavior So in the degenerate regime, which we call it the order state. You're gonna have the phase being locked to the phase of the pump as I talked about in the non the general regime. However, the phase is the phase is mostly dominated by the quantum diffusion off the off the phase, which is limited by the so called shallow towns limit and you can see that transition from the general to non degenerate, which also has distinct symmetry differences. And this transition corresponds to a symmetry breaking in the non degenerate case. The signal can acquire any of those phases on the circle, so it has a you one symmetry. And if you go to the degenerate case, then that symmetry is broken and you only have zero pie face days I will look at So now the question is can utilize this phase transition, which is a face driven phase transition and can we use it for similar computational scheme? So that's one of the questions that were also thinking about. And it's not just this face transition is not just important for computing. It's also interesting from the sensing potentials and this face transition. You can easily bring it below threshold and just operated in the quantum regime. Either Gaussian or non Gaussian. If you make a network of Opio is now, we can see all sorts of more complicated and more interesting phase transitions in the spectral domain. One of them is the first order phase transition, which you get by just coupling to oppose. And that's a very abrupt face transition and compared to the to the single Opio face transition. And if you do the couplings right, you can actually get a lot of non her mission dynamics and exceptional points, which are actually very interesting to explore both in the classical and quantum regime. And I should also mention that you can think about the cup links to be also nonlinear couplings. And that's another behavior that you can see, especially in the nonlinear in the non degenerate regime. So with that, I basically told you about these Opio networks, how we can think about the linear scheme and the linear behaviors and how we can think about the rich, nonlinear dynamics and non linear behaviors both in the classical and quantum regime. I want to switch gear and tell you a little bit about the miniaturization of these Opio networks. And of course, the motivation is if you look at the electron ICS and >>what we had 60 or 70 years ago with vacuum tube and how we transition from relatively small scale computers in the order of thousands of nonlinear elements to billions of non linear elements, where we are now with the optics is probably very similar to seven years ago, which is a tabletop implementation. >>And the question is, how can we utilize nano photonics? I'm gonna just briefly show you the two directions on that which we're working on. One is based on lithium Diabate, and the other is based on even a smaller resonate er's Did you? So the work on Nana Photonic lithium naive. It was started in collaboration with Harvard Marko Loncar and also might affair at Stanford. And, uh, we could show that you can do the >>periodic polling in the phenomenon of it and get all sorts of very highly non in your process is happening in this net. Photonic periodically polls if, um Diabate >>and now we're working on building. Opio was based on that kind of photonic lithium Diabate and these air some some examples of the devices that we have been building in the past few months, which I'm not gonna tell you more about. But the OPI ohs and the Opio networks are in the works, and that's not the only way of making large networks. But also I want to point out that the reason that these Nana photonic goblins are actually exciting is not just because you can make a large networks and it can make him compact in a in a small footprint, they also provide some opportunities in terms of the operation regime. On one of them is about making cat states in o pos, which is can we have the quantum superposition of >>the zero pie states that I talked about >>and the nano photonics within? I would provide some opportunities to actually get >>closer to that regime because of the spatial temporal confinement that you can get in these wave guides. So we're doing some theory on that. We're confident that the type of non linearity two losses that it can get with these platforms are actually much higher than what you can get with other platform, other existing platforms and to >>go even smaller. We have been asking the question off. What is the smallest possible Opio that you can make? Then you can think about really wavelength scale type resonate er's and adding the chi to non linearity and see how and when you can get the Opio to operate. And recently, in collaboration with us. See, we have been actually USC and Creole. We have demonstrated that you can use nano lasers and get some spin Hamiltonian implementations on those networks. So if you can't build a pos, we know that there is a path for implementing Opio Networks on on such a nano scale. So we have looked at these calculations and we try to >>estimate the threshold of a pos. Let's say for me resonator and it turns out that it can actually be even lower than the type of bulk Pippen O pos that we have been building in the past 50 years or so. >>So we're working on the experiments and we're hoping that we can actually make even larger and larger scale Opio networks. So let me summarize the talk I told you about the opium networks and >>our work that has been going on on icing machines and the >>measurement feedback on I told you about the ongoing work on the all optical implementations both on the linear side and also on the nonlinear behaviors. And I also told you >>a little bit about the efforts on miniaturization and going to the to the nano scale. So with that, I would like Thio stop here and thank you for your attention.

>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen brought to you by bread. >> Welcome back to the Cube. Continuing coverage here read. Had some twenty nineteen day three of our three days of covering some nine thousand attendees, great keynotes, great educational sessions and a couple of great guests for you to meddle. And John Walls were joined by Marco Bill Peter, who is the senior vice president of customer experience and engagement at Red Hat. Good to see you, Marco. Thanks for having the job on the keynote stage this morning. And Dr Christoph back, who was the head of infrastructure from Hilty and Christof. Thank you for being here is Well, thankyou. Hailing from from election Stein. And we think you're the first guest alum were to check our database, But But we've set a new record today. So thanks for adding to our having. First off, let's talk about Hilty. I'm sure people don't stay healthy. I've seen them, but this building probably wouldn't be here without you. Have imagined half the city wouldn't be here without you. But just tell folks at home a healthy a little bit about where you fit into the construction. >> Lt was founded in the nineteen forties in principality of a Lichtenstein as and is now today leading supplier for the construction industry. We provide tours, consumables, services and software solutions for professional construction companies. Daddy's from hammer drills, two anchors to calculation software and overall complete services for the industry. That's what hell is doing. >> So you did a very good job this morning on the keynote of painting that picture about about the scope of your work and the necessity of your work, the vitality of it. Because construction projects, as we all know, how very strict deadlines. Sometimes they have unique needs. They have immediate needs emergency needs, and you're in the center of all that. And so your technology is central to your general operation. >> Absolutely yes. I mean, with twenty five thousand or twenty nine thousand employees, twenty five thousand users in our system, basically, everybody's using everyday ASAP or the fast majority of users. We have ten thousand concurrent users every day on our system. That deal with customer requests with orders with quotes, but also, of course, with complaints with repair handling and so on. In >> just a few. Yeah, just >> so Marco, I hear ASAP and, you know, bring me back to when? Oh, well, you know, Lennox was that stuff that sat on little sidelines. We're well past that. You've got so many customers that run their business, you know, mission critical around the globe. Just give give, give us a little bit of background on the partnership with Hilty and Red Hat and Solutions like asap. >> Yes, sure. Yeah. The Department of Hilty goes back to, I think, two thousand seven for me. Personally, I started working with Hilton for another company in ninety three. So I know where the hell did Quite well, actually studied in the same town next to Lichtenstein, Son of the mail. And And it's it's amazing to see the journey kind of two thousand nine going all s ap mission critical on rail and now actually moved to Asa P s for Han. And yes, Hill is one ofthe declines. But it kind of talks that we can handle this mission. Critical applications are mission critical customers and built this good relationship to make sure they have these these courage to actually do this Bold jumps limited The last six months. >> Christoph, you know you've got a broad, you know, roll at the at the company way talked to so many companies on becoming a tech company on becoming a software company. Well, software is critical, but at the end of the day, you know, infrastructure and running your business is core. You know, you're not going to become a fully digital software. You have real stuff in the physical world that lots of people and lots of, you know, physical things that need to go to a little bit about that balance. And now the company has been changing over those last ten years. >> I was excited to be open with you. I was really excited when our executive board a couple of years ago, besides tools, consumables and services also added software into a strategic pillar for Hilty. Um, and while I believe that software will be an interesting pillar for us, well will generate additional revenue, will generate additional sales from early. Also in the consumables and tools and services piece software becomes more and more important when you look at the journey off building a building like this. As you mentioned John, I mean it starts with specifying it starts with the planning on CD, and it ends at the end with with Asset Management. Where are the tours and so on. So it's a complete life cycle through out the building off off throughout the construction of ah building. You >> know, Marco had mentioned that you made this decision to migrate Ohana last year right? Twenty eighteen or or where he might be rated last year? Isn't last year's decision made before that? Talk about that a little bit, if you would please and where Red Hat fit into that? Because that that's that's not a small decision, right? I mean, that's a That's a very calculated and I wouldn't not risky, but it's It's just a big move. Yeah, and so the confidence that you had a CZ well, that red hat was your partner to make that happen. >> Absolutely. I mean, the announcement of SAPI to support Hana as thie only database after twenty twenty five voice one off the factors to push us into that direction, that that was then clear for us that we want to go there. And it was also pretty clear for us that in our size it was not that easy to move in twenty twenty three or something like that in that direction, but that we have to be the first movers to be fully supported by ASAP and >> all >> these Parkins because later on, they will be busy with migrating all the big shots. So Wade took the decision to move first and soon, and that allowed us to be in the focus off all thes attached partners ASAP. But also read had also tell emcee for storage and HP for for servers. That meant that we had confidence that we have full attention from all these providers and partners to help us to migrate. On the other hand, it was clear the the the journey we started in two thousand nine has indicated by Marko that we moved to an open software that we move to commodity hardware. Intel based server hardware was a move that had paid off in the past, and we didn't want to go away from that and move again to a proprietary hardware or software solutions. So it was very clear that we want to do that jointly with red hat on commodity and until based service and That's how we went there, Right? >> So, Christophe, big theme, we hear not only at this show, but almost every show we go to is today customers. It's, you know, the hybrid and multi cloud world I see ASAP at all of the Big Cloud shows that that that we cover well, we're just cloud fit into your over discussion, you know, at your company. And then, you know, we can drill down to the specifics of that sapien red hat. But it's what do you have? A cloud strategy, as it were? >> Oh, yes, you know, we moved fairly soon to Amazon with all our customer facing workload. So when you go to hilton dot com or any of our Web pages, you typically land on a ws powered website because that one gave us the flexibility off operating systems off databases of whatever we needed. That was that was available there with our internal workload. However, So all the software we use Internet eternally toe run the company. We have a world that is split between ASAP, which runs entirely on Red hat, um, and the rest of the workload. Witches to a large degree, windows based workload so there. We decided a few years ago to Movinto Microsoft Azure platform to move the internal workload into Azure as it is mainly Windows based. >> So Marco actually want one a depart from healthy for a second. Just give us a little bit of a broad view. You know, we've talked to you many times. You talked about the stage. You know, the customer experiences a critical piece of red hats mission out there When I talk to customers today, One of the biggest changes they've seen the last few years is I'm managing a lot of stuff that's not in my environment. It's the stuff I'm responsible for it and something goes wrong. I'm absolutely getting a call, but you know, it's not my network. It's not my servers. It's not my piece there, but I have to do all of them, you know, got imagine. That's been a transformation for red Hat in the partnerships, and you're everywhere, so it just gets a little context. Yeah, I >> mean, you described it very well, right? I mean, I think the last two years before, I think it was just like some use cases in the public club. But today. The harder cloud is here, right? And everybody does it right. It's not like just one company from a customer experience to stand behind. Like I mentioned it on the state gets harder. Right? And you gonna have these partnerships, right? One partnership, right. We can talk about the azure. We have people in enrichment, right? Think about it today. And then everything changed with start having on stage here. But we have support people in micro for the last two or three years, right? Same diff ASAP as an example, right? We have people. We actually build a fairly large teeming, involved off to be close of us. Time together. I want to do that speed ASAP. A cloud bead on regular bear closes in general. Yes, That challenges. You mentioned networking, right? It gets tricky, right? And he shifted from, but it's unavoidable, right? It shifted from, like, okay, we own and control the stacked kind of too. Yes, you need to know you're open source after and to have really partnerships. Right? And I think the announcement Microsoft, too have this managed services offering that we do joint. It's That's what we're driving so that we can do this better together with partners. >> Marco is great to hear you that but Christoph, he's not listening. Tell us to reality. You've worked with Red Hat for ten years. You're going to cloud how they doing? How's the ecosystem, the vendors in general? They're all up on stage, holding hands. I mean, it's it's seamless and nobody ever point fingers. I'm sure >> to be very, very honest with you. I mean, I appreciate it last year, hearing that redhead will be offered in Azure. I mean, that was not possible to mention those two company names in one sentence in the past, at least for us as customers, and that that was a bold statement last year that those two parties will suddenly join. That fits very well in our strategy, because we believe internal workload for Hilton should run in in In Azure seeing on last Tuesday, Microsoft and Red Hat shaking hands and movie. Even beyond that one was, for me, them almost the most exciting event here, or the most exciting statement that I saw here during these few days because that reemphasized the close relationship that those two have, and that exactly fits our road map. That's exciting. >> And, you know, we heard that, you know, again from from both CEO Saying customers really kind of brought us together. They made this deal work because we kept hearing that they love us and they love you, and they like us together. So So we got that. We understand that. So? So Marco customers drove that to a certain degree. You've got a customer here who made this big Hana jump, which is you say small guy. You know, I would beg to differ little bit that you had him before the big guys did. But what, like an initiative like that? What is that doing for you? What? Red hat. In terms of carrying that over to other customers. Now, you've learned from one you've seen what they've gone through. What kind of confidence does that give you? What kind of interest does it give you about how to approach this game? >> Absolutely. You know what we learned from give you one example right? If you moved his heart ever closer Christopher Hilty uses systems have twelve terabytes memory. Think about it that fairly large systems and that foot train tried to actually test our softer with that footprint and then even think about the next. Next journey is in if you want to do this in the cloud. What does that mean? If you take a twelve terabyte image and running in a double? Yes. And so that is, since my team also does quality assurance and product security. That's for them as well as in. Okay, we've seen what tilted can do work. How do we actually make this more robust? How do we test you are there? And how do we do that in this journey? It's, I think I'm pretty proud of how we actually learn from these instances, and health is not the only one. It's just one the republic. But yet it's every time. I think that's the only survived is into industry. If you really learn continuously and also applied right. I mean our whole setup involved or we shifted completely and not just from the people. They have theirs. So we have people that do open. Chief. There were people do Lennox and performance, but also from structure. I really be sure that they were set up for success and know what the next they have customers is obviously every casting off. A message we will do will go through a journey license over the next ten years. >> Kristoff obviously being on stage, you know it is good for the company, but coming to Red Hat Summit one. Just give our audience that if they hadn't come to it. Some of the value is, too what you place in some, the activities that have excited you most here this week. >> I mean, one thing is, of course, hearing about latest technologies, new releases, off software, off new possibilities and opportunities for us as customers from Red Hat. But also, it's great to see how on the floor out there other partners customers on DH fingers mingle around the ecosystem that created that was created around open software about, ah, not only operating system, but also about containers about all these those different technologies, which I have an important role for all of us in nineteen the future. >> Sure. Well, good week, that's for sure. Very nice job you get on the Kino stage to both of you and good luck with the partnership on down the road. And again, I would make the difference that way. little guys got in early hilt. He's no small fry in inner world, that's for sure. Thanks for the time, Krystof. Marco. Thank you. Thank you very much. Back with more. We're live here in Boston and we're covering the red hat. Summer twenty nineteen on the

[Music] and y'all know that these [Music] ladies and gentlemen please take your seats and silence your cellphone's our program will begin shortly ladies and gentlemen please welcome Red Hat executive vice president and chief people officer dallisa Alexander an executive vice president and chief marketing officer Tim Layton [Music] hi everyone we're so excited to kick off this afternoon day 2 at the Red Hat summit we've got a stage full of stories about people making amazing contributions with open source well you know dallisa you and I both been coming to this event for a long long time so what keeps you coming back well you know the summit started as a tech conference an amazing tech conference but now it's expanded to be so much more this year I'm really thrilled that we're able to showcase the power of open source going way beyond the data center and beyond the cloud and I'm here also on a secret mission oh yes I'm here to make sure you don't make too many bad dad jokes so there's no such thing as a bad dad they're just dad jokes are supposed to be bad but I promise to keep it to my limit but I do have one okay I may appeal to the geeks in the audience okay so what do you call a serving tray full of empty beer cans yeah we container platform well that is your one just the one that's what I only got a budget of one all right well you know I have to say though in all seriousness I'm with you yeah I've been coming to the summit since its first one and I always love to hear what new directions people are scoring what ideas they're pursuing and the perspectives they bring and this afternoon for example you're gonna hear a host of different perspectives from a lot of voices you wouldn't often see on a technology mainstage in our industry and it's all part of our open source series live and I have to say there's been a lot of good buzz about this session all week and I'm truly honored and inspired to be able to introduce them all later this afternoon I can tell you over the course the last few weeks I've spent time with all of them and every single one of them is brilliant they're an innovator they're fearless and they will restore your faith in the next generation you know I can't wait to see all these stories all of that and we've got some special guests that are surprised in store for us you know one of the things that I love about the people that are coming on the stage today with us is that so many of them teach others how to code and they're also bringing more people that are very different in to our open-source communities helping our community is more innovative and impactful and speaking of innovative and impactful that's the purpose of our open brand project right that's right we're actually in the process of exploring a refresh of our mark and we'd really like your help as well because we're doing this all in the open we've we've been doing it already in the open and so please join us in our feedback zone booth at the summit to tell us what you think now it's probably obvious but I'm big into Red Hat swag I've got the shirt I've got my pen I've got the socks so this is really important to me personally especially that when my 15 year old daughter sees me in my full regalia she calls me adorable okay that joke was fed horrible as you're done it wasn't it wasn't like I got way more well Tim thanks for helping us at this stage for today it's time to get started with our first guest all right I'll be back soon thank you the people I'm about to bring on the stage are making outstanding contributions to open source in new and brave ways they are the winners of the 2018 women and open source Awards the women in open source awards was created to highlight the contributions that women are making to open source and to inspire new generations to join the movement our judges narrowed down the panel a very long list just ten finalists and then the community selected our two winners that were honoring today let's learn a little bit more about them [Music] a lot of people assume because of my work that I must be a programmer engineer when in fact I specifically chose and communications paths for my career but what's fascinating to me is I was able to combine my love of Communications and helping people with technology and interesting ways I'm able to not be bound by the assumptions that everybody has about what the technology can and should be doing and can really ask the question of what if it could be different I always knew I wanted to be in healthcare just because I feel like has the most impact in helping people a lot of what I've been working on is geared towards developing technology and the health space towards developing world one of the coolest things about open-source is bringing people together working with other people to accomplish amazing things there's so many different projects that you could get involved in you don't even have to be the smartest person to be able to make impact when you're actually developing for someone I think it's really important to understand the need when you're pushing innovation forward sometimes the cooler thing is not [Music] for both of us to have kind of a health care focus I think it's cool because so many people don't think about health care as being something that open-source can contribute to it took a while for it to even get to the stage where it is now where people can open-source develop on concepts and health and it's an untapped potential to moving the world for this award is really about highlighting the work of dozens of women and men in this open source community that have made this project possible so I'm excited for more people to kind of turn their open-source interest in healthcare exciting here is just so much [Music] I am so honored to be able to welcome to the stage some brilliant women and opensource first one of our esteemed judges Denise Dumas VP of software engineering at Red Hat she's going to come up and share her insights on the judging process Denise so you've been judging since the very beginning 2015 what does this judge this being a judge represents you what does the award mean to you you know every year it becomes more and more challenging to select the women an opensource winner because every year we get more nominees and the quality of the submissions well there are women involved in so many fabulous projects so the things that I look for are the things that I value an open source initiative using technology to solve real world problems a work ethic that includes sin patches and altruism and I think that you'll see that this year's nominees this year's winners really epitomize those qualities totally agree shall we bring them on let's bring them on let's welcome to the stage Zoe de gay and Dana Lewis [Music] [Applause] [Applause] [Music] alright let's take a seat [Applause] well you both have had an interesting path to open-source zuy you're a biomedical engineering student any of it you have a degree in public relations tell us what led to your involvement and open source yeah so coming to college I was new I was interested in science but I didn't want to be a medical doctor and I didn't want to get involved in wet lab research so through classes I was taking oh that's why I did biomedical engineering and through classes I was taking I found the classroom to be very dry and I didn't know how how can I apply what I'm learning and so I got involved in a lot of entrepreneurship on campus and through one of the projects I was asked to build a front end and I had no idea how to go about doing that and I had some basic rudimentary coding knowledge and what happened was I got and was digging deep and then found an open source library that was basically building a similar thing that I needed and that was where I learned about open source and I went from there now I'm really excited to be able to contribute to many communities and work on a variety of projects amazing contributions Dana tell us about your journey well I come from a non-traditional background but I was diagnosed with type 1 diabetes at the age of 14 and over the next couple years got really frustrated with the limitations of my own diabetes devices but felt like I couldn't change them because that wasn't my job as a patient but it was actually through social media I discovered someone who had solved one of the problems that I had been found having which was getting date off my diabetes device and that's how I learned about open source was when he was willing to share his code with me so when we turned around and made this hybrid closed-loop artificial pancreas system it was a no brainer to make our work open source as well that's right absolutely and we see using the hash tag we are not waiting can you tell us about that yeah so this hash tag was created actually before I even discovered the open source diabetes world but I loved it because it really illustrates exactly the fact that we have this amazing technology in our hands in our pockets and we can solve some of our most common problems so yes you could wait but waiting is now a choice with open source we have the ability to solve some of our hardest problems even problems dealing with life and death that's great so zuy with the vaccine carrier system that you helped to build how were you able to identify the need and where did you build it yes so I think before you even build anything first need to understand what is the problem that you're trying to solve and that really was the case when starting this project I got to collaborate with engineers in Kampala Uganda and travel there and actually interview stakeholders in the medical field medical doctors as well as pharmaceutical companies and from there I really got to understand the health system there as well as what is how do vaccines enter the country and how can we solve this problem and that's how we came up with the solution for an IOT based vaccine carrier tracking system I think it's really important especially today when products might be flashy to also understand what is the need behind it and how do we solve problems with these products yeah yeah it's so interesting how both of you have this interest in health care Dana how do you see open-source playing a role in healthcare but first before you answer that tell us about your shirt so this shirt has the code of my artificial pancreas on it and I love it as an illustration of no thank you I love it as an illustration of how open-source is more than we think it is I've just been blown away by the contributions of people in my open-source communities and I think that that is what we should apply to all of healthcare there's a lot of tools and technologies that are solving real world problems and I think if we take what we know in technology and apply it to healthcare we'll solve a lot of problems more quickly but it really needs to be recognizing everything an open source it's the documentation it's the collaboration it's the problem-solving it's working together to take technologies that we didn't previously think we're applicable and finding new ways to apply it it's a great answer Sooey yeah I think especially where healthcare is related to people and open-source is the right way to collaborate with people all over the world especially in the project I've been working on we're looking at vaccines in Uganda but the same system can be applied in any other country and then you can look at cross countries health systems there and from there it becomes bigger and bigger and I think it's really important for people who have an idea and want to take it further to know that open-source is a way that you could actually take your idea further whether you have a technical background or not so yeah stories are amazing you're just an inspiration for everyone in open-source I want to thank you so much for joining us here today let's give another round of applause to our winners [Applause] [Music] you know the tagline for the award is honor celebrate inspire and I feel like we've been doing that today very very well and I know that so many people have been inspired today especially the next generation who go on to do things we can't even dream of yet [Music] I think collabs important because we need to make sure we get younger children interested in technology so that they understand the value of it but also that there are a lot of powerful women in technology and they can be one of them I hope after this experience maybe we'll get some engineers and some girls working our hot so cool right well we have some special guests convite for the club stage now I'd like to invite Tim back and also introduce Red Hat's own Jamie Chappell along with our collab students please welcome Gabby tenzen Sofia lyric Camila and a Volyn [Applause] you've been waiting for this moment for a while we're so excited hear all about your experiences but Jamie first tell us about collab sure so collab is red hats way of teaching students about the power of open source and collaboration we kicked off a little over a year ago in Boston and that was so successful that we decided to embark on an East Coast tour so in October we made stops at middle schools in New York DC and Raleigh and these amazing people over here are from that tour and this week they have gone from student to teacher so they've hosted two workshops where they have taught Red Hat summit attendees how to turn raspberry pies into digital cameras they assigned a poem song of the open road by Walt Whitman and they've been working at the open source stories booth helping to curate photos for an installation we're excited to finish up tomorrow so amazing and welcome future women in open source we want to know all about your experiences getting involved can you tell us tenzen tell us about something you've learned so during my experience with collab I learned many things but though however the ones that I valued the most were open source and women empowerment I just I was just so fascinated about how woman were creating and inventing things for the development of Technology which was really cool and I also learned about how open source OH was free and how anyone could access it and so I also learned that many people could you know add information to it so that other people could you learn from it and use it as well and during Monday's dinner I got this card saying that the world needed more people like you and I realized through my experience with collab that the world does not only need people like me but also everyone else to create great technology so ladies you know as you were working on your cameras and the coding was there a moment in time that you had an AHA experience and I'm really getting this and I can do this yes there was an aha moment because midway through I kind of figured out well this piece of the camera went this way and this piece of the camera did it go that way and I also figured out different features that were on the camera during the camera build I had to aha moments while I was making my camera the first one was during the process of making my camera where I realized I was doing something wrong and I had to collaborate with my peers in order to troubleshoot and we realize I was doing something wrong multiple times and I had to redo it and redo it but finally I felt accomplished because I finished something I worked hard on and my second aha moment was after I finished building my camera I just stared at it and I was in shock because I built something great and it was so such a nice feeling so we talked a lot about collaboration when we were at the lab tell us about how learning about collaboration in the lab is different than in school so in school collaboration is usually few and far between so when we went to collab it allowed us to develop new skills of creativity and joining our ideas with others to make something bigger and better and also allowed us to practice lots of cooperation an example of this is in my group everybody had a different problem with their pie camera and we had to use our different strengths to like help each other out and everybody ended up assembling and working PI camera great great awesome collaboration in collab and the school is very different because in collab we were more interactive more hands-on and we had to work closer together to achieve our own goals and collaboration isn't just about working together but also combining different ideas from different people to get a product that is so much better than some of its parts so girls one other interesting observation this actually may be for the benefit of the folks in our audience but out here we have represented literally hundreds and hundreds of companies all of whom are going to be actually looking for you to come to work for them after today we get first dibs that's right but um you know if you were to have a chance to speak to these companies and say what is it that they could do to help inspire you know your your friends and peers and get them excited about open source what would you say to them well I'm pretty sure we all have app store and I'm pretty sure we've all downloaded an app on that App Store well instead of us downloading app State well the computer companies or the phone companies they could give us the opportunity to program our own app and we could put it on the App Store great idea absolutely I've got to tell you I have a 15 year old daughter and I think you're all going to be an inspiration to her for the same absolutely so much so I see you brought some cameras why don't we go down and take a picture let's do it [Applause] all right I will play my very proud collab moderator role all right so one two three collab okay one two three [Applause] yeah so we're gonna let leave you and let you tell us more open source stories all right well thank you great job thank you all and enjoy the rest of your time at Summit so appreciate it thanks thank you everyone pretty awesome pretty awesome and I would just like to say they truly are fedorable that's just um so if you would like to learn more as you heard the girls say they're actually Manning our open-source stories booth at the summit you know please come down and say hello the stories you've seen thus far from our women and open-source winners as well as our co-op students are really bringing to life the theme of this year's summit the theme of ideas worth exploring and in that spirit what we'd like to do is explore another one today and that is how open-source concepts thrive and expand in the neverending organic way that they do much like the universe metaphor that you see us using here it's expanding in new perspectives and new ideas with voices beyond their traditional all starting to make open-source much bigger than what it was originally started as fact open-source goes back a long way long before actually the term existed in those early days you know in the early 80s and the like most open-source projects were sort of loosely organized collections of self-interested developers who are really trying to build low-cost more accessible replicas of commercial software yet here we are 2018 the world is completely different the open-source collaborative development model is the font of almost all original new innovation in software and they're driven from communities communities of innovation RedHat of course has been very fortunate to have been able to build an extraordinary company you know whose development model is harnessing these open-source innovations and in turning them into technologies consumable by companies even for their most mission-critical applications the theme for today though is we see open-source this open source style collaboration and innovation moving beyond just software this collaborative community innovation is starting to impact many facets of society and you're starting to see that even with the talks we've had already too and this explosion of community driven innovation you know is again akin to this universe metaphor it expands in all directions in a very organic way so for red hat you know being both beneficiaries of this approach and stewards of the open collaboration model we see it important for us to give voice to this broader view of open source stories now when we say open source in this context of course will meaning much more than just technology it's the style of collaboration the style of interaction it's the application of open source style methods to the innovation process it's all about accelerating innovation and expanding knowledge and this can be applied to a whole range of human endeavors of course in education as we just saw today on stage in agriculture in AI as the open source stories we shared at last year's summit in emerging industries like healthcare as we just saw in manufacturing even the arts all these are areas that are now starting to benefit from collaboration in driving innovation but do we see this potentially applying to almost any area of human endeavor and it expands again organically expanding existing communities with the addition of new voices and new participants catalyzing new communities and new innovations in new areas as we were talking about and even being applied inside organizations so that individual companies and teams can get the same collaborative innovation effects and most profound certainly in my perspective is so the limitless bounds that exist for how this open collaboration can start to impact some of humankind's most fundamental challenges we saw a couple of examples in fact with our women and open-source winners you know that's amazing but it also potentially is just the tip of the iceberg so we think it's important that these ideas you know as they continue to expand our best told through storytelling because it's a way that you can embrace them and find your own inspirations and that's fundamentally the vision behind our open-source stories and it's all about you know building on what's come before you know the term we use often is stay the shoulders are giants for a lot of the young people that you've seen on this stage and you're about to see on this stage you all are those giants you're the reason and an hour appears around the world are the reasons that open-source continues to expand for them you are those giants the other thing is we all particularly in this room those of us have been around open-source we have an open-source story of our own you know how were you introduced the power of open-source how did you engage a community who inspired you to participate those are all interesting elements of our personal open-source stories and in most cases each of them are punctuated by you here my question to the girls on stage an aha moment or aha moments you know that that moment of realization that enlightens you and causes you to think differently and to illustrate I'm going to spend just a few minutes sharing my open-source story for for one fundamental reason I've been in this industry for 38 years I am a living witness to the entire life of open-source going back to the early 80s I've been doing this in the open-source corner of the industry since the beginning if you've listened to Sirhan's command-line heroes podcasts my personal open story will actually be quite familiar with you because my arc is the same as the first several podcast as she talked about I'm sort of a walking history lesson in fact of open source I wound up at most of the defining moments that should have changed how we did this not that I was particularly part of the catalyst I was just there you know sort of like the Forrest Gump of open-source I was at all these historical things but I was never really sure how it went up there but it sure was interesting so with that as a little bit of context I'm just gonna share my aha moment how did I come to be you know a 59 year old in this industry for 38 years totally passionate about not just open source driving software innovation but what open source collaboration can do for Humanity so in my experience I had three aha moments I just like to share with you the first was in the early 80s and it was when I was introduced to the UNIX operating system and by the way if you have a ha moment in the 80s this is what it looks like so 1982 mustache 19 where were you 2018 beard that took a long time to do all right so as I said my first aha moment was about the technology itself in those early days of the 80s I became a product manager and what at the time was digital equipment corporation's workstation group and I was immediately drawn to UNIX I mean certainly these this is the early UNIX workstation so the user interface was cool but what I really loved was the ability to do interactive programming via the shell but by a--basically the command line and because it was my day job to help figure out where we took these technologies I was able to both work and learn and play all from the same platform so that alone was was really cool it was a very accessible platform the other thing that was interesting about UNIX is it was built with networking and and engagement in mind had its own networking stack built in tcp/ip of course and actually built in a set of services for those who've been around for a while think back to things like news groups and email lists those were the first enablers for cross internet collaboration and that was really the the elements that really spoke to me he said AHA to me that you know this technology is accessible and it lets people engage so that was my first aha moment my second aha moment came a little bit later at this point I was an executive actually running Digital Equipment Corporation UNIX systems division and it was at a time where the UNIX wars were raging right all these companies we all compartmentalized Trump those of the community and in the end it became an existential threat to the platform itself and we came to the point where we realized we needed to actually do something we needed to get ahead of this or UNIX would be doomed the particular way we came together was something called cozy but most importantly the the technique we learned was right under our noses and it was in the area of distributed computing distributed client-server computing inherently heterogenous and all these same companies that were fierce competitors at the operating system level were collaborating incredibly well around defining the generation of client-server and distributed computing technologies and it was all being done in open source under actually a BSD license initially and Microsoft was a participant Microsoft joined the open group which was the converged standards body that was driving this and they participated to ensure there was interoperability with Windows and and.net at the time now it's no spoiler alert that UNIX lost right we did but two really important things came out of that that sort of formed the basis of my second aha moment the first is as an industry we were learning how to collaborate right we were leveraging open source licenses we realized that you know these complex technologies are best done together and that was a huge epiphany for the industry at that time and the second of course is that event is what opened the door for Linux to actually solve that problem so my second aha was all about the open collaboration model works now at this point to be perfectly candidates late 1998 well we've been acquired by compacts when I'm doing the basically same role at Compaq and I really had embraced what the potential impact of this was going to be to the industry Linux was gaining traction there were a lot of open source projects emerging in distributed computing in other areas so it was pretty clear to me that the in business impact was going to be significant and and that register for me but there was seem to be a lot more to it that I hadn't really dropped yet and that's when I had my third aha moment and that was about the passion of open-source advocates the people so you know at this time I'm running a big UNIX group but we had a lot of those employees who were incredibly passionate about about Linux and open source they're actively participating so outside of working a lot of things and they were lobbying more and more for the leadership to embrace open source more directly and I have to say their passion was contagious and it eventually spread to me you know they were they were the catalyst for my personal passion and it also led me to rethink what it is we needed to go do and that's a passion that I carry forward to this day the one driven by the people and I'll tell you some interesting things many of those folks that were with us at Compaq at the time have gone on to be icons and leaders in open-source today and many of them actually are involved with with Red Hat so I'll give you a couple of names that some of whom you will know so John and Mad Dog Hall work for me at the time he was the person who wrote the first edition of Linux for dummies he did that on his own time when he was working for us he he coined he was part of the small team that coined the term open source' some other on that team that inspired me Brian Stevens and Tim Burke who wrote the first version to rent out Enterprise Linux actually they did that in Tim Burke's garage and cost Tim's still with Red Hat today two other people you've already seen him on stage today Denise Dumas and Marko bill Peter so it was those people that I was fortunate enough to work with early on who had passion for open-source and much like me they carry it forward to this day so the punchline there is they ultimately convinced us to you know embrace open-source aggressively in our strategy and one of the interesting things that we did as a company we made an equity investment in Red Hat pre-ipo and a little funny sidebar here I had to present this proposal to the compact board on investing in Red Hat which was at that time losing money hand over fist and they said well Tim how you think they're gonna make money selling free software and I said well you know I don't really know but their customers seem to love them and we need to do this and they approve the investment on the spot so you know how high do your faith and now here we are at a three billion dollar run rate of this company pretty extraordinary so from me the third and final ha was the passion of the people in the way it was contagious so so my journey my curiosity led me first to open source and then to Red Hat and it's been you know the devotion of my career for over the last thirty years and you know I think of myself as pretty literate when it comes to open source and software but I'd be the first one to admit I would have never envisioned the extent to which open source style collaboration is now being brought to bear on some of the most interesting challenges in society so the broader realization is that open source and open can really unlock the world's potential when applied in the collaborative innovative way so what about you you know you many of you particular those have been around for a while you probably have an open source story of your own for those that maybe don't or they're new to open source are new to Red Hat your open source story may be a single inspiration away it may happen here at the summit we certainly hope so it's how we build the summit to engage you you may actually find it on this stage when I bring up some of the people who are about to follow me but this is why we tell open-source stories and open source stories live so each of you hopefully has a chance to think about you know your story and how it relates over source so please take advantage of all the things that are here at the summit and and find your inspiration if you if you haven't already so next thing is you know in a spirit of our telling open source stories today we're introducing our new documentary film the science of collective discovery it's really about citizen scientists using open systems to do serious science in their backyards and environmental areas and the like we're going to preview that I'm gonna prove it preview it today and then please come see it tonight later on when we preview the whole video so let's take a look I may not have a technical scientific background but I have one thing that the scientists don't have which is I know my backyard so conventional science happens outside of public view so it's kind of in this black box so most are up in the ivory tower and what's exciting about citizen science is that it brings it out into the open we as an environmental community are engaging with the physical world every day and you need tools to do that we needed to democratize that technology we need to make it lightweight we need to make it low-cost we needed to make it open source so that we could put that technology in the hands of everyday people so they go out and make those measurements where they live and where they breathe when you first hear about an environmental organization you mostly hear about planting trees gardens things like that you don't really think about things that are really going to affect you hey we're the air be more they'd hold it in their hand making sure not to cover the intake or the exhaust I just stand here we look at the world with forensic eyes and then we build what you can't see so the approach that we're really centered on puts humans and real issues at the center of the work and I think that's the really at the core of what open source is social value that underlies all of it it really refers to sort of the rights and responsibilities that anyone on the planet has to participate in making new discoveries so really awesome and a great story and you know please come enjoy the full video so now let's get on with our open stories live speakers you're going to really love the rest of the afternoon we have three keynotes and a demo built in and I can tell you without exaggeration that when you see and hear from the young people we're about to bring forward you know it's truly inspirational and it's gonna restore totally your enthusiasm for the future because you're gonna see some of the future leaders so please enjoy our open source stories live presentation is coming and I'll be back to join you in a little bit thanks very much please welcome code newbie founder Saran yep Eric good afternoon how y'all doing today oh that was pretty weak I think you could do better than that how y'all doing today wonderful much better I'm Saran I am the founder of code newbie we have the most supportive community of programmers and people learning to code this is my very first Red Hat summits I'm super pumped super excited to be here today I'm gonna give you a talk and I'm going to share with you the key to coding progress yes and in order to do that I'm gonna have to tell you a story so two years ago I was sitting in my hotel room and I was preparing for a big talk the next morning and usually the night before I give a big talk I'm super nervous I'm anxious I'm nauseous I'm wondering why I keep doing this to myself all the speakers backstage know exactly what I'm what I'm talking about and the night before my mom knows this so she almost always calls just to check in to see how I'm doing to see how I'm feeling and she called about midnight the night before and she said how are you how are you doing are you ready and I said you know what this time I feel really good I feel confident I think I'm gonna do a great job and the reason was because two months ago I'd already given that talk in fact just a few days prior they had published the video of that talk on YouTube and I got some really really good positive feedback I got feedback from emails and DMS and Twitter and I said man I know people really like this it's gonna be great in fact that video was the most viewed video of that conference and I said to my office said you know what let's see how many people loved my talk and still the good news is that 14 people liked it and a lot more people didn't and I saw this 8 hours before I'm supposed to give that exact same talk and I said mom I gotta call you back do you like how I did that to hang up the phone as if that's how cellphones work yeah and so I looked at this and I said oh my goodness clearly there's a huge disconnect I thought they were really liked they were I thought they were into it and this showed me that something was wrong what do you do what do you do when you're about to give that same talk in 8 hours how do you begin finding out what the problem is so you can fix it I have an idea let's read the comments you got to believe you gotta have some optimism come on I said let's read the comments because I'm sure we'll find some helpful feedback some constructive criticism some insights to help me figure out how to make this talk great so that didn't happen but I did find some really colorful language and some very creative ideas of what I could do with myself now there are some kids in the audience so I will not grace you with these comments but there was this one comment that did a really great job of capturing the sentiment of what everyone else was saying I can only show you the first part because the rest is not very family-friendly but it reads like this how do you talk about coding and not fake societal issues see the thing about that talk is it wasn't just a code talk it was a code and talk is about code and something else that talked touched on code and social justice I talked a lot about how the things that we build the way we build them affect real people and their problems and their struggles and that was absolutely not okay not okay we talk about code and code only not the social justice stuff it also talked about code and diversity yeah I think we all know the diversity is really about lowering the bar it forces us to talk about people and their issues and their problems in their history and we just don't do that okay absolutely inappropriate when it comes to a Tech Talk That Talk touched on code and feelings and feelings are squishy they're messy they're icky and a lot of us feel uncomfortable with feelings feelings have no place in technology no place in code we want to talk about code and code I want you to show me that API and when you show me that new framework that new tool that's gonna solve my problems that's all I care about I want to talk about code and give me some more code with it now I host a podcast called command line heroes it's an original podcast from Red Hat super excited about it if you haven't checked it out and totally should and what I love about this show as we talk about these really important moments and open swords these inflection points moments where we see progress we move forward and what I realized looking back at those episodes is all of those episodes have a code and something let's look at a few of those the first two episodes focused on the history of operating systems as a two-part episode part 1 and part 2 and there's lots of different ways we can talk about operating systems for these two episodes we started by talking about Windows and Mac OS and how these were two very powerful very popular operating systems but a lot of a lot of developers were frustrated with them they were closed you couldn't see inside you can see what it was doing and I the developer want to know what it's doing on my machine so we kind of had a little bit of a war one such developer who was very frustrated said I'm gonna go off and do my own thing my name is Linus this thing is Linux and I'm gonna rally all these other developers all these other people from all over the old to come together and build this new thing with me that is a code and moment in that case it was code and frustration it was a team of developers a world of developers literally old world of developers who said I'm frustrated I'm fed up I want something different and I'm gonna do something about it and what's really beautiful about frustration is it the sign of passion we're frustrated because we care because we care so much we love so deeply then we want to do something better next episode is the agile revolution this one was episode three now the agile revolution is a very very important moment in open-source and technology in general and this was in response to the way that we used to create products we used to give this huge stack of specs all these docs from the higher-ups and we'd take it and we go to our little corner and we lightly code and build and then a year with Pastor here's a pass a few years have passed and we'd finally burst forth with this new product and hope that users liked it and loved it and used it and I know something else will do that today it's okay no judgment now sometimes that worked and a lot of times it didn't but whether or not it actually worked it hurt it was painful these developers not enjoy this process so what happened a dozen developers got together and literally went off into their own and created something called the agile manifesto now this was another code and moment here it's code and anger these developers were so angry that they literally left civilization went off into a mountain to write the agile manifesto and what I love about this example is these developers did not work at the same company we're not on the same team they knew each other from different conferences and such but they really came from different survive and they agreed that they were so angry they were going to literally rewrite the way we created products next as an example DevOps tear down the wall this one is Episode four now this is a bit different because we're not talking about a piece of technology or even the way we code here we're talking about the way we work together the way that we collaborate and here we have our operations folks and our developers and we've created this new kind of weird place thing called DevOps and DevOps is interesting because we've gotten to a point where we have new tools new toys so that our developers can do a lot of the stuff that only the operations folks used to be able to do that thing that took days weeks months to set up I can do it with a slider it's kind of scary I can do it with a few buttons and here we have another code and moment and here that blink is fear for two reasons the operations focus is looking over the developer folks and thinking that was my job I used to be able to do that am I still valuable do I have a place in this future do I need to retrain there's also another fear which is those developers know what they're doing do they understand the security implications they appreciate how hard it is or something to scale and how to do that properly and I'm really interested in excited to see where we go with that where we take that emotion if we look at all of season one of the podcast we see that there's always a code and whether it's a code and frustration a code and anger or a code and fear it always boils down to code and feelings feelings are powerful in almost every single episode we see that that movement forward that progress is tied back to some type of Oshin and for a lot of us this is uncomfortable feelings make us feel weird and a lot of those YouTube commenters definitely do not like this whole feeling stuff don't be like those YouTube commenters there's one thing you take away from this whole talk let it be that don't be like these YouTube commenters feelings are incredibly powerful so the next time that you're working on a project you're having a conversation about a piece of software or a new piece of technology and you start to get it worked up you get angry you get frustrated maybe you get worried you get anxious you get scared I hope you recognize that feeling as a source of energy I hope you take that energy and you help us move forward I would take that to create the next inflection point that next step in the right direction feelings are your superpowers and I hope you use your powers for good thank you so much [Applause] please welcome jewel-box chief technology officer Sara Chipps [Music] Wow there's a lot of you out here how's it going I know there's a lot of you East Coasters here as well and I'm still catching up on that sleep so I hope you guys are having a great experience also my name is Sarah I'm here from New York I have been a software developer for 17 years it's longer than some of the people on stage today I've been alive big thanks to the folks at Red Hat for letting us come and tell you a little bit about jewel box so without further ado I'm gonna do exactly that okay so today we're gonna do a few things first I'm gonna tell you why we built jewel BOTS and why we think it's a really important technology I'm gonna show you some amazing magic and then we're gonna have one of the jewel bus experts come as a special guest and talk to you more about the deep technology behind what we're building so show hands in the audience who here was under 18 years old when they started coding it's hard for me to see you guys yep look around I'd have to say at least 50% of you have your hands up all right keep your hand up if you were under 15 when you started coding I think more hands up just what is it I don't know how that mouth works but awesome okay great yeah a little of I think about half of you half of you have your hands up that's really neat I've done a bunch of informal polls on the internet about this I found that probably about two-thirds of professional coders were under 18 when they started coding I myself was 11 I was a homeschooled kid so a little weird I'm part of the generation and some of you maybe as well is the reason we became coders is because we were lonely not because we made a lot of money so I was 11 this is before the internet was a thing and we had these things called BBS's and you would call up someone else's computer in your town and you would hang out with people and chat with them and play role-playing games with them it didn't have to be your town but if it wasn't your mom would yell at you for a long distance fees and I got really excited about computers and coding because of the community that I found online okay so this is sometimes the most controversial part of this presentation I promised you that they dominate our lives in many ways even if you don't even if you don't even know a 9 to 14 year old girl even if you just see them on the street sometimes they are deciding what you and I do on a regular basis hear me out for a second here so who here knows who this guy is okay you don't have to raise your hands but I think most people know who this guy is right so this guy used to be this guy and then teenage girls were like I think this guy has some talent to him I think that he's got a future and now he's a huge celebrity today what about this guy just got his first Oscar you know just kind of starting out well this guy used to be this guy and I'm proud to tell you that I am one of the many girls that discovered him and decided this guy has a future all right raise your hand if you listen to Taylor Swift just kidding I won't make you do it but awesome that's great so Taylor Swift we listen to Taylor Swift because these girls discovered Taylor Swift it wasn't a 35 year old that was like this Taylor Swift is pretty neat no one cares what we think but even bigger than that these huge unicorns that all of us some of us work for some of us wish we invented these were discovered by young teenage girls no one is checking to see what apps were using they're finding new communities in these thin in these platforms and saying this is how I want to commune with my friends things like Instagram snapchat and musically all start with this demographic and then we get our cues from them if you don't know what musically is I promise you ask your nearest 9 to 14 year old friend if you don't do that you'll hear about it in a few years but this demographic their futures are all at risk everyone here knows how much the field of software development is growing and how important technical literacy is to the future of our youth however just 18% of computer science graduates are girls just 19% of AP computer science test takers and just 15% of Google's tech force identify as female so we decided to do something about that we were inspired by platforms like MySpace and Geocities things like Neopets and minecraft all places where kids find something they love and they're like okay to make this better all I have to do is learn how to code I can totally do that and so we wanted to do that so we talked to 200 girls we went to schools we sat down with them and we were like what makes you tick what are you excited about and what we heard from them over and over again is their friends their friends and their community are pivotal to them and this time in their lives so when we started talking to them about a smart friendship bracelet that's when they started really freaking out so we built Jewel BOTS and Jewel BOTS has an active online community where girls can work together share code that they've built and learn from each other help each other troubleshoot sometimes the way they work is when you are near your friends your bracelets light up the same color and you can use them to send secret messages to each other and you can also code them so you can say things like when all my swimming friends are together in the same room all of our bracelets should go rainbow colors which is really fun you can even build games jewel BOTS started shipping about a year and a half ago about after a lot of work and we are about to ship our 12,000 jewel bot we're in 38 city sorry 38 countries and we're just getting started okay so now it's time for the magic and I have an important question does anyone here want to be my friend pick me all right someone today Gary oh I don't have many friends that's awesome I'm so glad that we'll be friends okay it's awesome so we just need to pair our jewel BA okay okay and in order to do that we're gonna hold the magic button in the middle down for two seconds so one locomotive two locomotive great and then we got a white flashing I'm gonna do yours again I did it wrong locomotive two locomotive it's we're adults we can't do it okay it's a good that are smart alright so now we get to pick our friendship color I'm gonna pick red hat red does that work for you sure okay great so now I just picked a red hat red and my jewel bot is saying alright Tim's jewel bot do you want to be my friend and imageable about it's like I'm thinking about it I think so okay now we're ready okay great so now we're red friends when we're together our bracelets are going to be red and I will send you a secret message when it's time for you to come out and trip and introduce the next guest awesome well thank you so much thank you tailor gun so glad we could be friends and if only people would start following me on Twitter it'd be a great day awesome alright so now you can see the not so technical part of jewel box they use bluetooth to sense when your friends are nearby so they would work in about a 30 meter hundred foot range but to tell you about the actual technology part I'm going to introduce is someone much more qualified than I am so Ellie is one of our jewel box ambassadors she's an amazing YouTube channel that I would please ask you to check out and subscribe she's le G Joel BOTS on YouTube she's an amazing coder and I'm really excited to introduce you today to Ellie Galloway come on out Ellie [Applause] hello my name is le gallais I'm gonna show you how I got coding and then show you some coding in action I first started coding at a6 when my dad helped me code a game soon after I program form a code for Minecraft then my dad had shown me jo bot I keep coding because it helps people for instance for instance you could code auto crack to make it a lot smarter so it can help make people stay run faster but what about something more serious what if you could help answer 911 calls and give alerts before we start I have three main steps to share with you I often use these steps to encoding my jaw bot and continue to use some of these now step one read the instructions and in other words this means for Jabba to memorize the colors and positions a way to memorize these because it's tricky is to remember all the colors and positions you O type will be capital and remember that the positions are either short for north west south west north east and south east step to learn the basic codes when it comes to coding you need to work your way up step 3 discover feel free to discover once you mastered everything now let's get to coding let's use or let's first use combining lights so under void loop I'm going to put LED turn on single s/w and blue and before we make sure that this works we got to put LED LED okay now let's type this again LED dot turn on single now let's do SW green now we have our first sketch so let's explain what this means led LED is a function that to control the LED lights LED turn on single SW blue tells that SW light to turn blue and green flashes so quickly with the blue it creates aqua now let's do another code lets you i'm going to use a more advanced command to make a custom color using RGB let's use a soft pink using 255 105 and 180 now let's type this in the button press function so let's do LED led LED dot set light and now we can do let's do position 3 255 105 and 180 now let's explain what this means the first one stands for the position the three others stand for red green and blue our GPS can only go up to 255 but there are 256 levels but if you count the first one as zero then get 255 so let's first before we move on let's show how this works so this is it before and now let's turn it on to see how our aqua turned out now let's see how our RGB light turned out so we are looking for a soft pink so let's see how it looks think about how much the code you write can help people all around the world these are ideas are just the beginning of opening a new world in technology a fresh start is right around the corner I hope this helped you learn a little bit about coding and even made you want to try it out for yourself thank you [Applause] alright alright alright I need your help for a second guys alright one second really really fascinating we're short on time today is Ellie's 11th birthday and I think we should give her the biggest present that she's gonna get today and it's something none of us have experienced and that is thousands of people saying happy birthday Elliott wants so when I say three can I get a happy birthday Elly one two three happy birthday Elly great job that's the best part of my job okay so those are that's two of us we're just getting started this numbers out Dana would almost shipped 12,000 jewel BOTS and what I'm really excited to tell you about is that 44% of our users don't just play with their jewel bots they code them and they're coding C do you even code C I don't know that you do but we have 8 to 14 year olds coding C for their jewel box we also have hundreds of events where kids come and they learn how to code for the first time here's how you can help we're open source so check out our github get involved our communities online you can see the different features that people's are asking for we're also doing events all over the world a lot of people are hosting them at their companies if you're interested in doing so reach out to us thank you so much for coming and learning about jewel box today enjoy the rest of your summit [Music] ladies and gentlemen please welcome hacker femme au founder Femi who Bois de Kunz [Music] good afternoon red hat summit 2018 i'm femi holiday combs founder of hacker femme Oh I started coding when I was 8 when I was 9 I set up South London raspberry jam through crowdfunding to share my passion for coding with other young people who might not otherwise be exposed to tech since then I've run hundreds of coding and robot workshops across the UK and globally in 2017 I was awarded an inaugural legacy Diana award by their Royal Highnesses Prince William and Prince Harry my service and community we welcome young people who have autism or like me tract syndrome because coding linked me up to a wider community of like-minded people and I'm trying to do the same for those who might also benefit from this I also deliver workshops to corporate companies and public organizations whilst feeding back ideas and resources into my community work we like to cascade our knowledge and experience to other young coders so that they can benefit too we're learning new tech every day we're starting to use github to document and manage our coding projects we've no dread we're using the terminal and beginning to really appreciate Linux as we explore cybersecurity and blockchain it's been quite a journey from South London to the world-famous Tate Modern museum to Bangladesh to this my first trip to the States and soon to China where I hope to translate my microwave workshops into Mandarin on this journey I'm noticed it is increasingly important for young coders to have collaborative and community led initiatives and enterprise and career ready skills so my vision now is to run monthly meetups and in collaboration with business partners help a hundred young disadvantaged people to get jobs in the digital services in fact out of all the lessons I've learned from teaching young coders they all have one thing in common the power of open source and the importance of developing community and today I want to talk about three of those lessons the value of reaching out and collaborating the importance of partnering event price and the ability to self organize and persist which translated into English means having a can-do attitude getting stuff done when you reach out when you show curiosity you realize you're not alone in this diverse community no matter who you are and where you're from from coding with minecraft to meeting other young people with jams I found there are people like me doing things I like doing I get to connect with them that's where open-source comes to the fourth second the open source community is so vast then it crosses continents it's so immersed perspectives that it can take you to amazing places out of space even that's my code running on the International Space Station's Columbus module let's take a lesson and playing was an audio representation for the frequencies recorded in space my team developed Python code to measure and store frequency readings from the space station and that was down linked back to earth to my email box Thomas who's 10 developed an audio file using audacity and importing it back into Python how cool is that Trulli collaboration can take you places you never thought possible because that's how the community works when you throw a dilemma a problem a tip the open source community comes back with answers when you give the community gives back tenfold that's how open source expands but in that vast starscape how do you know what to focus on there are so many problems to solve where do I start your world enterprice enterprise software is very good at solving problems what's the big problem how about helping the next generation be ready for the future I want to do more for the young coding community so I'm developing entrepreneurial business links to get that done this is a way to promote pathways to deal with future business problems whether in FinTech healthcare or supply chains a meeting the skill shortage it is a case for emerging in it's a case for investing in emerging communities and young change enablers throwing a wider net equates to being fully inclusive with a good representation of diversity you know under the shadow of the iconic show back in London there are pockets of deprivation where young people can't even get a job in a supermarket many of them are interested in tech in some way so my goal for the next three years is to encourage young people to become an active part of the coding community with open source we have the keys to unlock the potential for future innovation and technological development with young coders we have the people who have to face these problems working on them now troubleshooting being creative connecting with each other finding a community discovering their strengths along the way for me after running workshops in the community for a number of years when I returned from introducing coding to young street kids in Bangladesh I realized I had skills and experience so I set up my business hacker Famicom my first monetized fehmi's coding boot camp at Rice London Barclays Bank it was a sellout and a few weeks later shows my second I haven't looked back since but it works the opposite way - all the money raised enable me to buy robots for my community events and I was able to cascade my end price knowledge across to other young coders - when you focus on business problems you get active enthusiastic support from enterprise and then you can take on anything the support is great and we have tons of ideas but what does it really take to execute on those ideas to get things done can-do attitudes what open source needs you've seen it all this week we're all explorers ideator z' thinkers and doers open source needs people who can make the ideas happen get out there and see them through like I did setting up Safford and raspberry jam as an inclusive space to collaborate and learn together and that that led to organizing the young coders conference this was about organizing our own two-day event for our partners in industry to show they value young people and wanted to invest in our growth it doesn't stop there oh nice now I'm setting up monthly coding meetups and looking at ways to help other young people to access job opportunities in end price and digital services the underlying ethos remains the same in all I do promoting young people with the desire to explore collaborative problem-solving when coding digital making and building enterprise you fled having the confidence to define our journey and pathways always being inclusive always encouraging innovation and creativity being doers does more than get projects done makes us a pioneering force in the community dreaming and doing is how we will make exponential leaps my generation is standing on the shoulders of giants you the open-source pioneers and the technology you will built so I'd love to hear about your experiences who brought you into the open-source community who taught you as we go to upscale our efforts we encounter difficulties have you and how did you overcome them please do come to talk to me I'll be in the open-source stories booth both today and tomorrow giving workshops or visit the Red Hat page of my website hack Famicom I really value your insights in conclusion I'd like I'd like to ask you to challenge yourself you can do this by supporting young coders find the crowdfunding campaign kick-start their ideas into reality I'm proof that it works it's so awesome to be an active part of the next exponential leap together thank you [Applause] so unbelievable huh you know he reminds me of be at that age not even close and I can tell you I've spent a lot of time with Femi and his mom grace I mean what you see is what you get I mean he's incredibly passionate committed and all that stuff he's doing that long list of things he's doing he's going to do so hopefully today you get a sense of what's coming in the next generation the amazing things that people are doing with collaboration I'd also like to thank in addition to femi I'd like to thank Sauron Sarah and Ellie for equally compelling talks around the open source stories and again as I mentioned before any one of you can have an open source story that can be up here inspiring others and that's really our goal in telling these stories and giving voice to the things that you've seen today absolutely extraordinary things are happening out there and I encourage you to take every advantage you can hear this week and as is our theme for the summit please keep exploring thank you very much [Applause] [Music]

[Music] [Music] [Music] [Music] [Music] [Music] that will be successful in the 21st century [Music] being open is really important because it comes with a lot of trust the open-source community now has matured so much and that contribution from the community is really driving innovation [Music] but what's really exciting is the change that we've seen in our teams not only the way they collaborate but the way they operate in the way they work [Music] I think idea is everything ideas can change the way you see things open-source is more than a license it's actually a way of operating [Music] ladies and gentlemen please welcome Red Hat president and chief executive officer Jim Whitehurst [Music] all right well welcome to day two at the Red Hat summit I'm amazed to see this many people here at 8:30 in the morning given the number of people I saw pretty late last night out and about so thank you for being here and have to give a shout out speaking of power participation that DJ is was Mike Walker who is our global director of open innovation labs so really enjoyed that this morning was great to have him doing that so hey so day one yesterday we had some phenomenal announcements both around Red Hat products and things that we're doing as well as some great partner announcements which we found exciting I hope they were interesting to you and I hope you had a chance to learn a little more about that and enjoy the breakout sessions that we had yesterday so yesterday was a lot about the what with these announcements and partnerships today I wanted to spin this morning talking a little bit more about the how right how do we actually survive and thrive in this digitally transformed world and to some extent the easy parts identifying the problem we all know that we have to be able to move more quickly we all know that we have to be able to react to change faster and we all know that we need to innovate more effectively all right so the problem is easy but how do you actually go about solving that right the problem is that's not a product that you can buy off the shelf right it is a capability that you have to build and certainly it's technology enabled but it's also depends on process culture a whole bunch of things to figure out how we actually do that and the answer is likely to be different in different organizations with different objective functions and different starting points right so this is a challenge that we all need to feel our way to an answer on and so I want to spend some time today talking about what we've seen in the market and how people are working to address that and it's one of the reasons that the summit this year the theme is ideas worth it lorring to take us back on a little history lesson so two years ago here at Moscone the theme of the summit was the power of participation and then I talked a lot about the power of groups of people working together and participating are able to solve problems much more quickly and much more effectively than individuals or even individual organizations working by themselves and some of the largest problems that we face in technology but more broadly in the world will ultimately only be solved if we effectively participate and work together then last year the theme of the summit was the impact of the individual and we took this concept of participation a bit further and we talked about how participation has to be active right it's a this isn't something where you can be passive that you can sit back you have to be involved because the problem in a more participative type community is that there is no road map right you can't sit back and wait for an edict on high or some central planning or some central authority to tell you what to do you have to take initiative you have to get involved right this is a active participation sport now one of the things that I talked about as part of that was that planning was dead and it was kind of a key my I think my keynote was actually titled planning is dead and the concept was that in a world that's less knowable when we're solving problems in a more organic bottom-up way our ability to effectively plan into the future it's much less than it was in the past and this idea that you're gonna be able to plan for success and then build to it it really is being replaced by a more bottom-up participative approach now aside from my whole strategic planning team kind of being up in arms saying what are you saying planning is dead I have multiple times had people say to me well I get that point but I still need to prepare for the future how do I prepare my organization for the future isn't that planning and so I wanted to spend a couple minutes talk a little more detail about what I meant by that but importantly taking our own advice we spent a lot of time this past year looking around at what our customers are doing because what a better place to learn then from large companies and small companies around the world information technology organizations having to work to solve these problems for their organizations and so our ability to learn from each other take the power of participation an individual initiative that people and organizations have taken there are just so many great learnings this year that I want to get a chance to share I also thought rather than listening to me do that that we could actually highlight some of the people who are doing this and so I do want to spend about five minutes kind of contextualizing what we're going to go through over the next hour or so and some of the lessons learned but then we want to share some real-world stories of how organizations are attacking some of these problems under this how do we be successful in a world of constant change in uncertainty so just going back a little bit more to last year talking about planning was dead when I said planning it's kind of a planning writ large and so that's if you think about the way traditional organizations work to solve problems and ultimately execute you start off planning so what's a position you want to get to in X years and whether that's a competitive strategy in a position of competitive advantage or a certain position you want an organizational function to reach you kind of lay out a plan to get there you then typically a senior leaders or a planning team prescribes the sets of activities and the organization structure and the other components required to get there and then ultimately execution is about driving compliance against that plan and you look at you say well that's all logical right we plan for something we then figure out how we're gonna get there we go execute to get there and you know in a traditional world that was easy and still some of this makes sense I don't say throw out all of this but you have to recognize in a more uncertain volatile world where you can be blindsided by orthogonal competitors coming in and you the term uber eyes you have to recognize that you can't always plan or know what the future is and so if you don't well then what replaces the traditional model or certainly how do you augment the traditional model to be successful in a world that you knows ambiguous well what we've heard from customers and what you'll see examples of this through the course of this morning planning is can be replaced by configuring so you can configure for a constant rate of change without necessarily having to know what that change is this idea of prescription of here's the activities people need to perform and let's lay these out very very crisply job descriptions what organizations are going to do can be replaced by a greater degree of enablement right so this idea of how do you enable people with the knowledge and things that they need to be able to make the right decisions and then ultimately this idea of execution as compliance can be replaced by a greater level of engagement of people across the organization to ultimately be able to react at a faster speed to the changes that happen so just double clicking in each of those for a couple minutes so what I mean by configure for constant change so again we don't know exactly what the change is going to be but we know it's going to happen and last year I talked a little bit about a process solution to that problem I called it that you have to try learn modify and what that model try learn modify was for anybody in the app dev space it was basically taking the principles of agile and DevOps and applying those more broadly to business processes in technology organizations and ultimately organizations broadly this idea of you don't have to know what your ultimate destination is but you can try and experiment you can learn from those things and you can move forward and so that I do think in technology organizations we've seen tremendous progress even over the last year as organizations are adopting agile endeavor and so that still continues to be I think a great way for people to to configure their processes for change but this year we've seen some great examples of organizations taking a different tack to that problem and that's literally building modularity into their structures themselves right actually building the idea that change is going to happen into how you're laying out your technology architectures right we've all seen the reverse of that when you build these optimized systems for you know kind of one environment you kind of flip over two years later what was the optimized system it's now called a legacy system that needs to be migrated that's an optimized system that now has to be moved to a new environment because the world has changed so again you'll see a great example of that in a few minutes here on stage next this concept of enabled double-clicking on that a little bit so much of what we've done in technology over the past few years has been around automation how do we actually replace things that people were doing with technology or augmenting what people are doing with technology and that's incredibly important and that's work that can continue to go forward it needs to happen it's not really what I'm talking about here though enablement in this case it's much more around how do you make sure individuals are getting the context they need how are you making sure that they're getting the information they need how are you making sure they're getting the tools they need to make decisions on the spot so it's less about automating what people are doing and more about how can you better enable people with tools and technology now from a leadership perspective that's around making sure people understand the strategy of the company the context in which they're working in making sure you've set the appropriate values etc etc from a technology perspective that's ensuring that you're building the right systems that allow the right information the right tools at the right time to the right people now to some extent even that might not be hard but when the world is constantly changing that gets to be even harder and I think that's one of the reasons we see a lot of traction and open source to solve these problems to use flexible systems to help enterprises be able to enable their people not just in it today but to be flexible going forward and again we'll see some great examples of that and finally engagement so again if execution can't be around driving compliance to a plan because you no longer have this kind of Cris plan well what do leaders do how do organizations operate and so you know I'll broadly use the term engagement several of our customers have used this term and this is really saying well how do you engage your people in real-time to make the right decisions how do you accelerate a pace of cadence how do you operate at a different speed so you can react to change and take advantage of opportunities as they arise and everywhere we look IT is a key enabler of this right in the past IT was often seen as an inhibitor to this because the IT systems move slower than the business might want to move but we are seeing with some of these new technologies that literally IT is becoming the enabler and driving the pace of change back on to the business and you'll again see some great examples of that as well so again rather than listen to me sit here and theoretically talk about these things or refer to what we've seen others doing I thought it'd be much more interesting to bring some of our partners and our customers up here to specifically talk about what they're doing so I'm really excited to have a great group of customers who have agreed to stand in front of 7,500 people or however many here this morning and talk a little bit more about what they're doing so really excited to have them here and really appreciate all them agreeing to be a part of this and so to start I want to start with tee systems we have the CEO of tee systems here and I think this is a great story because they're really two parts to it right because he has two perspectives one is as the CEO of a global company itself having to navigate its way through digital disruption and as a global cloud service provider obviously helping its customers through this same type of change so I'm really thrilled to have a del hasta li join me on stage to talk a little bit about T systems and what they're doing and what we're doing jointly together so Adelle [Music] Jim took to see you Adele thank you for being here you for having me please join me I love to DJ when that fantastic we may have to hire him no more events for events where's well employed he's well employed though here that team do not give him mics activation it's great to have you here really do appreciate it well you're the CEO of a large organization that's going through this disruption in the same way we are I'd love to hear a little bit how for your company you're thinking about you know navigating this change that we're going through great well you know key systems as an ICT service provider we've been around for decades I'm not different to many of our clients we had to change the whole disruption of the cloud and digitization and new skills and new capability and agility it's something we had to face as well so over the last five years and especially in the last three years we invested heavily invested over a billion euros in building new capabilities building new offerings new infrastructures to support our clients so to be very disruptive for us as well and so and then with your customers themselves they're going through this set of change and you're working to help them how are you working to help enable your your customers as they're going through this change well you know all of them you know in this journey of changing the way they run their business leveraging IT much more to drive business results digitization and they're all looking for new skills new ideas they're looking for platforms that take them away from traditional waterfall development that takes a year or a year and a half before they see any results to processes and ways of bringing applications in a week in a month etcetera so it's it's we are part of that journey with them helping them for that and speaking of that I know we're working together and to help our joint customers with that can you talk a little bit more about what we're doing together sure well you know our relationship goes back years and years with with the Enterprise Linux but over the last few years we've invested heavily in OpenShift and OpenStack to build peope as layers to build you know flexible infrastructure for our clients and we've been working with you we tested many different technology in the marketplace and been more successful with Red Hat and the stack there and I'll give you an applique an example several large European car manufacturers who have connected cars now as a given have been accelerating the applications that needed to be in the car and in the past it took them years if not you know scores to get an application into the car and today we're using open shift as the past layer to develop to enable these DevOps for these companies and they bring applications in less than a month and it's a huge change in the dynamics of the competitiveness in the marketplace and we rely on your team and in helping us drive that capability to our clients yeah do you find it fascinating so many of the stories that you hear and that we've talked about with with our customers is this need for speed and this ability to accelerate and enable a greater degree of innovation by simply accelerating what what we're seeing with our customers absolutely with that plus you know the speed is important agility is really critical but doing it securely doing it doing it in a way that is not gonna destabilize the you know the broader ecosystem is really critical and things like GDP are which is a new security standard in Europe is something that a lot of our customers worry about they need help with and we're one of the partners that know what that really is all about and how to navigate within that and use not prevent them from using the new technologies yeah I will say it isn't just the speed of the external but the security and the regulation especially GDR we have spent an hour on that with our board this week there you go he said well thank you so much for being here really to appreciate the work that we're doing together and look forward to continued same here thank you thank you [Applause] we've had a great partnership with tea systems over the years and we've really taken it to the next level and what's really exciting about that is you know we've moved beyond just helping kind of host systems for our customers we really are jointly enabling their success and it's really exciting and we're really excited about what we're able to to jointly accomplish so next i'm really excited that we have our innovation award winners here and we'll have on stage with us our innovation award winners this year our BBVA dnm IAG lasat Lufthansa Technik and UPS and yet they're all working in one for specific technology initiatives that they're doing that really really stand out and are really really exciting you'll have a chance to learn a lot more about those through the course of the event over the next couple of days but in this context what I found fascinating is they were each addressing a different point of this configure enable engage and I thought it would be really great for you all to hear about how they're experimenting and working to solve these problems you know real-time large organizations you know happening now let's start with the video to see what they think about when they think about innovation I define innovation is something that's changing the model changing the way of thinking not just a step change improvement not just making something better but actually taking a look at what already exists and then putting them together in new and exciting lives innovation is about to build something nobody has done before historically we had a statement that business drives technology we flip that equation around an IT is now demonstrating to the business at power of technology innovation desde el punto de vista de la tecnología supone salir de plataform as proprietary as ADA Madero cloud basado an open source it's a possibility the open source que no parameter no sir Kamala and I think way that for me open-source stands for flexibility speed security the community and that contribution from the community is really driving innovation innovation at a pace that I don't think our one individual organization could actually do ourselves right so first I'd like to talk with BBVA I love this story because as you know Financial Services is going through a massive set of transformations and BBVA really is at the leading edge of thinking about how to deploy a hybrid cloud strategy and kind of modular layered architecture to be successful regardless of what happens in the future so with that I'd like to welcome on stage Jose Maria Rosetta from BBVA [Music] thank you for being here and congratulations on your innovation award it's been a pleasure to be here with you it's great to have you hi everybody so Josemaria for those who might not be familiar with BBVA can you give us a little bit of background on your company yeah a brief description BBVA is is a bank as a financial institution with diversified business model and that provides well financial services to more than 73 million of customers in more than 20 countries great and I know we've worked with you for a long time so we appreciate that the partnership with you so I thought I'd start with a really easy question for you how will blockchain you know impact financial services in the next five years I've gotten no idea but if someone knows the answer I've got a job for him for him up a pretty good job indeed you know oh all right well let me go a little easier then so how will the global payments industry change in the next you know four or five years five years well I think you need a a Weezer well I tried to make my best prediction means that in five years just probably will be five years older good answer I like that I always abstract up I hope so I hope so yah-yah-yah hope so good point so you know immediately that's the obvious question you have a massive technology infrastructure is a global bank how do you prepare yourself to enable the organization to be successful when you really don't know what the future is gonna be well global banks and wealth BBBS a global gam Bank a certain component foundations you know today I would like to talk about risk and efficiency so World Bank's deal with risk with the market great the operational reputational risk and so on so risk control is part of all or DNA you know and when you've got millions of customers you know efficiency efficiency is a must so I think there's no problem with all these foundations they problem the problem analyze the problems appears when when banks translate these foundations is valued into technology so risk control or risk management avoid risk usually means by the most expensive proprietary technology in the market you know from one of the biggest software companies in the world you know so probably all of you there are so those people in the room were glad to hear you say that yeah probably my guess the name of those companies around San Francisco most of them and efficiency usually means a savory business unit as every department or country has his own specific needs by a specific solution for them so imagine yourself working in a data center full of silos with many different Hardware operating systems different languages and complex interfaces to communicate among them you know not always documented what really never documented so your life your life in is not easy you know in this scenario are well there's no room for innovation so what's been or or strategy be BES ready to move forward in this new digital world well we've chosen a different approach which is quite simple is to replace all local proprietary system by a global platform based on on open source with three main goals you know the first one is reduce the average transaction cost to one-third the second one is increase or developers productivity five times you know and the third is enable or delete the business be able to deliver solutions of three times faster so you're not quite easy Wow and everything with the same reliability as on security standards as we've got today Wow that is an extraordinary set of objectives and I will say their world on the path of making that successful which is just amazing yeah okay this is a long journey sometimes a tough journey you know to be honest so we decided to partnership with the with the best companies in there in the world and world record we think rate cut is one of these companies so we think or your values and your knowledge is critical for BBVA and well as I mentioned before our collaboration started some time ago you know and just an example in today in BBVA a Spain being one of the biggest banks in in the country you know and using red hat technology of course our firm and fronting architecture you know for mobile and internet channels runs the ninety five percent of our customers request this is approximately 3,000 requests per second and our back in architecture execute 70 millions of business transactions a day this is almost a 50% of total online transactions executed in the country so it's all running yes running I hope so you check for you came on stage it's I'll be flying you know okay good there's no wood up here to knock on it's been a really great partnership it's been a pleasure yeah thank you so much for being here thank you thank you [Applause] I do love that story because again so much of what we talk about when we when we talk about preparing for digital is a processed solution and again things like agile and DevOps and modular izing components of work but this idea of thinking about platforms broadly and how they can run anywhere and actually delivering it delivering at a scale it's just a phenomenal project and experience and in the progress they've made it's a great team so next up we have two organizations that have done an exceptional job of enabling their people with the right information and the tools they need to be successful you know in both of these cases these are organizations who are under constant change and so leveraging the power of open-source to help them build these tools to enable and you'll see it the size and the scale of these in two very very different contexts it's great to see and so I'd like to welcome on stage Oh smart alza' with dnm and David Abraham's with IAG [Music] Oh smart welcome thank you so much for being here Dave great to see you thank you appreciate you being here and congratulations to you both on winning the Innovation Awards thank you so Omar I really found your story fascinating and how you're able to enable your people with data which is just significantly accelerated the pace with which they can make decisions and accelerate your ability to to act could you tell us a little more about the project and then what you're doing Jim and Tina when the muchisimas gracias por ever say interesado pono true projecto [Music] encargado registry controller las entradas a leda's persona por la Frontera argentina yo sé de dos siento treinta siete puestos de contrôle tienen lo largo de la Frontera tanto area the restreamer it EEMA e if looool in dilute ammonia shame or cinta me Jonas the tránsito sacra he trod on in another Fronteras dingus idea idea de la Magneto la cual estamos hablando la Frontera cantina tienen extension the kin same in kilo metros esto es el gada mint a maje or allege Estancia kaeun a poor carretera a la co de mexico con el akka a direction emulation s 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others in 2016 we shifted to a more preventive and predictive paradigm that is how Sam's the system for migration analysis was created with red hats great assistance and support this allowed us to tackle the challenge of integrating multiple and varied issues legal issues police databases national and international security organizations like Interpol API advanced passenger information and PNR passenger name record this involved starting private cloud with OpenShift Rev data virtualization cloud forms and fuse that were the basis to develop Sam and implementing machine learning models and artificial intelligence our analysts consulted a number of systems and other manual files before 2016 4 days for each person entering or leaving the country so this has allowed us to optimize our decisions making them in real time each time Sam is consulted it processes patterns of over two billion data entries Sam's aim is to improve the quality of life of our citizens and visitors making sure that crime doesn't pierce our borders in an environment of analytic evolution and constant improvement in essence Sam contributes toward Argentina being one of the leaders in Latin America in terms of immigration with our new system great thank you and and so Dave tell us a little more about the insurance industry and the challenges in the EU face yeah sure so you know in the insurance industry it's a it's been a bit sort of insulated from a lot of major change in disruption just purely from the fact that it's highly regulated and the cost of so that the barrier to entry is quite high in fact if you think about insurance you know you have to have capital reserves to protect against those major events like floods bush fires and so on but the whole thing is a lot of change there's come in a really rapid pace I'm also in the areas of customer expectations you know customers and now looking and expecting for the same levels of flexibility and convenience that they would experience with more modern and new startups they're expecting out of the older institutions like banks and insurance companies like us so definitely expecting the industry to to be a lot more adaptable and to better meet their needs I think the other aspect of it really is in the data the data area where I think that the donor is now creating a much more significant connection between organizations in a car summers especially when you think about the level of devices that are now enabled and the sheer growth of data that's that that's growing at exponential rates so so that the impact then is that the systems that we used to rely on are the technology we used to rely on to be able to handle that kind of growth no longer keeps up and is able to to you know build for the future so we need to sort of change that so what I G's really doing is transform transforming the organization to become a lot more efficient focus more on customers and and really set ourselves up to be agile and adaptive and so ya know as part of your Innovation Award that the specific set of projects you tied a huge amount of different disparate systems together and with M&A and other you have a lot to do there to you tell us a little more about kind of how you're able to better respond to customer needs by being able to do that yeah no you're right so we've we've we're nearly a hundred year old company that's grown from lots of merger and acquisition and just as a result of that that means that data's been sort of spread out and fragmented across multiple brands and multiple products and so the number one sort of issue and problem that we were hearing was that it was too hard to get access to data and it's highly complicated which is not great from a company from our perspective really because because we are a data company right that's what we do we we collect data about people what they what's important to them what they value and the environment in which they live so that we can understand that risk and better manage and protect those people so what we're doing is we're trying to make and what we have been doing is making data more open and accessible and and by that I mean making data more of easily available for people to use it to make decisions in their day-to-day activity and to do that what we've done is built a single data platform across the group that unifies the data into a single source of truth that we can then build on top of that single views of customers for example that puts the right information into the into the hands of the people that need it the most and so now why does open source play such a big part in doing that I know there are a lot of different solutions that could get you there sure well firstly I think I've been sauce has been k2 these and really it's been key because we've basically started started from scratch to build this this new next-generation data platform based on entirely open-source you know using great components like Kafka and Postgres and airflow and and and and and then fundamentally building on top of red Red Hat OpenStack right to power all that and they give us the flexibility that we need to be able to make things happen much faster for example we were just talking to the pivotal guys earlier this week here and some of the stuff that we're doing they're they're things quite interesting innovative writes even sort of maybe first in the world where we've taken the older sort of appliance and dedicated sort of massive parallel processing unit and ported that over onto red Red Hat OpenStack right which is now giving us a lot more flexibility for scale in a much more efficient way but you're right though that we've come from in the past a more traditional approach to to using vendor based technology right which was good back then when you know technology solutions could last for around 10 years or so on and and that was fine but now that we need to move much faster we've had to rethink that and and so our focus has been on using you know more commoditized open source technology built by communities to give us that adaptability and sort of remove the locking in there any entrenchment of technology so that's really helped us but but I think that the last point that's been really critical to us is is answering that that concern and question about ongoing support and maintenance right so you know in a regular environment the regulator is really concerned about anything that could fundamentally impact business operation and and so the question is always about what happens when something goes wrong who's going to be there to support you which is where the value of the the partnership we have with Red Hat has really come into its own right and what what it's done is is it's actually giving us the best of both worlds a means that we can we can leverage and use and and and you know take some of the technology that's being developed by great communities in the open source way but also partner with a trusted partner in red had to say you know they're going to stand behind that community and provide that support when we needed the most so that's been the kind of the real value out of that partnership okay well I appreciate I love the story it's how do you move quickly leverage the power community but do it in a safe secure way and I love the idea of your literally empowering people with machine learning and AI at the moment when they need it it's just an incredible story so thank you so much for being here appreciate it thank you [Applause] you know again you see in these the the importance of enabling people with data and in an old-world was so much data was created with a system in mind versus data is a separate asset that needs to be available real time to anyone is a theme we hear over and over and over again and so you know really looking at open source solutions that allow that flexibility and keep data from getting locked into proprietary silos you know is a theme that we've I've heard over and over over the past year with many of our customers so I love logistics I'm a geek that way I come from that background in the past and I know that running large complex operations requires flawless execution and that requires great data and we have two great examples today around how to engage own organizations in new and more effective ways in the case of lufthansa technik literally IT became the business so it wasn't enabling the business it became the business offering and importantly went from idea to delivery to customers in a hundred days and so this theme of speed and the importance of speed it's a it's a great story you'll hear more about and then also at UPS UPS again I talked a little earlier about IT used to be kind of the long pole in the tent the thing that was slow moving because of the technology but UPS is showing that IT can actually drive the business and the cadence of business even faster by demonstrating the power and potential of technology to engage in this case hundreds of thousands of people to make decisions real-time in the face of obviously constant change around weather mechanicals and all the different things that can happen in a large logistics operation like that so I'd like to welcome on stage to be us more from Lufthansa Technik and Nick Castillo from ups to be us welcome thank you for being here Nick thank you thank you Jim and congratulations on your Innovation Awards oh thank you it's a great honor so to be us let's start with you can you tell us a little bit more about what a viet are is yeah avatars are a digital platform offering features like aircraft condition analytics reliability management and predictive maintenance and it helps airlines worldwide to digitize and improve their operations so all of the features work and can be used separately or generate even more where you burn combined and finally we decided to set up a viet as an open platform that means that we avoid the whole aviation industry to join the community and develop ideas on our platform and to be as one of things i found really fascinating about this is that you had a mandate to do this at a hundred days and you ultimately delivered on it you tell us a little bit about that i mean nothing in aviation moves that fast yeah that's been a big challenge so in the beginning of our story the Lufthansa bot asked us to develop somehow digital to win of an aircraft within just hundred days and to deliver something of value within 100 days means you cannot spend much time and producing specifications in terms of paper etc so for us it was pretty clear that we should go for an angel approach and immediately start and developing ideas so we put the best experts we know just in one room and let them start to work and on day 2 I think we already had the first scribbles for the UI on day 5 we wrote the first lines of code and we were able to do that because it has been a major advantage for us to already have four technologies taken place it's based on open source and especially rated solutions because we did not have to waste any time setting up the infrastructure and since we wanted to get feedback very fast we were certainly visited an airline from the Lufthansa group already on day 30 and showed them the first results and got a lot of feedback and because from the very beginning customer centricity has been an important aspect for us and changing the direction based on customer feedback has become quite normal for us over time yeah it's an interesting story not only engaging the people internally but be able to engage with a with that with a launch customer like that and get feedback along the way as it's great thing how is it going overall since launch yeah since the launch last year in April we generated much interest in the industry as well from Airlines as from competitors and in the following month we focused on a few Airlines which had been open minded and already advanced in digital activities and we've got a lot of feedback by working with them and we're able to improve our products by developing new features for example we learned that data integration can become quite complex in the industry and therefore we developed a new feature called quick boarding allowing Airlines to integrate into the via table platform within one day using a self-service so and currently we're heading for the next steps beyond predictive maintenance working on process automation and prescriptive prescriptive maintenance because we believe prediction without fulfillment still isn't enough it really is a great example of even once you're out there quickly continuing to innovate change react it's great to see so Nick I mean we all know ups I'm still always blown away by the size and scale of the company and the logistics operations that you run you tell us a little more about the project and what we're doing together yeah sure Jim and you know first of all I think I didn't get the sportcoat memo I think I'm the first one up here today with a sport coat but you know first on you know on behalf of the 430,000 ups was around the world and our just world-class talented team of 5,000 IT professionals I have to tell you we're humbled to be one of this year's red hat Innovation Award recipients so we really appreciate that you know as a global logistics provider we deliver about 20 million packages each day and we've got a portfolio of technologies both operational and customer tech and another customer facing side the power what we call the UPS smart logistics network and I gotta tell you innovations in our DNA technology is at the core of everything we do you know from the ever familiar first and industry mobile platform that a lot of you see when you get delivered a package which we call the diad which believe it or not we delivered in 1992 my choice a data-driven solution that drives over 40 million of our my choice customers I'm whatever you know what this is great he loves logistics he's a my choice customer you could be one too by the way there's a free app in the App Store but it provides unmatched visibility and really controls that last mile delivery experience so now today we're gonna talk about the solution that we're recognized for which is called site which is part of a much greater platform that we call edge which is transforming how our package delivery teams operate providing them real-time insights into our operations you know this allows them to make decisions based on data from 32 disparate data sources and these insights help us to optimize our operations but more importantly they help us improve the delivery experience for our customers just like you Jim you know on the on the back end is Big Data and it's on a large scale our systems are crunching billions of events to render those insights on an easy-to-use mobile platform in real time I got to tell you placing that information in our operators hands makes ups agile and being agile being able to react to changing conditions as you know is the name of the game in logistics now we built edge in our private cloud where Red Hat technologies play a very important role as part of our overage overarching cloud strategy and our migration to agile and DevOps so it's it's amazing it's amazing the size and scale so so you have this technology vision around engaging people in a more effect way those are my word not yours but but I'd be at that's how it certainly feels and so tell us a little more about how that enables the hundreds of thousands people to make better decisions every day yep so you know we're a people company and the edge platform is really the latest in a series of solutions to really empower our people and really power that smart logistics network you know we've been deploying technology believe it or not since we founded the company in 1907 we'll be a hundred and eleven years old this August it's just a phenomenal story now prior to edge and specifically the syphon ishutin firm ation from a number of disparate systems and reports they then need to manually look across these various data sources and and frankly it was inefficient and prone to inaccuracy and it wasn't really real-time at all now edge consumes data as I mentioned earlier from 32 disparate systems it allows our operators to make decisions on staffing equipment the flow of packages through the buildings in real time the ability to give our people on the ground the most up-to-date data allows them to make informed decisions now that's incredibly empowering because not only are they influencing their local operations but frankly they're influencing the entire global network it's truly extraordinary and so why open source and open shift in particular as part of that solution yeah you know so as I mentioned Red Hat and Red Hat technology you know specifically open shift there's really core to our cloud strategy and to our DevOps strategy the tools and environments that we've partnered with Red Hat to put in place truly are foundational and they've fundamentally changed the way we develop and deploy our systems you know I heard Jose talk earlier you know we had complex solutions that used to take 12 to 18 months to develop and deliver to market today we deliver those same solutions same level of complexity in months and even weeks now openshift enables us to container raise our workloads that run in our private cloud during normal operating periods but as we scale our business during our holiday peak season which is a very sure window about five weeks during the year last year as a matter of fact we delivered seven hundred and sixty-two million packages in that small window and our transactions our systems they just spiked dramatically during that period we think that having open shift will allow us in those peak periods to seamlessly move workloads to the public cloud so we can take advantage of burst capacity economically when needed and I have to tell you having this flexibility I think is key because you know ultimately it's going to allow us to react quickly to customer demands when needed dial back capacity when we don't need that capacity and I have to say it's a really great story of UPS and red hat working you together it really is a great story is just amazing again the size and scope but both stories here a lot speed speed speed getting to market quickly being able to try things it's great lessons learned for all of us the importance of being able to operate at a fundamentally different clock speed so thank you all for being here very much appreciated congratulate thank you [Applause] [Music] alright so while it's great to hear from our Innovation Award winners and it should be no surprise that they're leading and experimenting in some really interesting areas its scale so I hope that you got a chance to learn something from these interviews you'll have an opportunity to learn more about them you'll also have an opportunity to vote on the innovator of the year you can do that on the Red Hat summit mobile app or on the Red Hat Innovation Awards homepage you can learn even more about their stories and you'll have a chance to vote and I'll be back tomorrow to announce the the summit winner so next I like to spend a few minutes on talking about how Red Hat is working to catalyze our customers efforts Marko bill Peter our senior vice president of customer experience and engagement and John Alessio our vice president of global services will both describe areas in how we are working to configure our own organization to effectively engage with our customers to use open source to help drive their success so with that I'd like to welcome marquel on stage [Music] good morning good morning thank you Jim so I want to spend a few minutes to talk about how we are configured how we are configured towards your success how we enable internally as well to work towards your success and actually engage as well you know Paul yesterday talked about the open source culture and our open source development net model you know there's a lot of attributes that we have like transparency meritocracy collaboration those are the key of our culture they made RedHat what it is today and what it will be in the future but we also added our passion for customer success to that let me tell you this is kind of the configuration from a cultural perspective let me tell you a little bit on what that means so if you heard the name my organization is customer experience and engagement right in the past we talked a lot about support it's an important part of the Red Hat right and how we are configured we are configured probably very uniquely in the industry we put support together we have product security in there we add a documentation we add a quality engineering into an organization you think there's like wow why are they doing it we're also running actually the IT team for actually the product teams why are we doing that now you can imagine right we want to go through what you see as well right and I'll give you a few examples on how what's coming out of this configuration we invest more and more in testing integration and use cases which you are applying so you can see it between the support team experiencing a lot what you do and actually changing our test structure that makes a lot of sense we are investing more and more testing outside the boundaries so not exactly how things must fall by product management or engineering but also how does it really run in an environment that you operate we run complex setups internally right taking openshift putting in OpenStack using software-defined storage underneath managing it with cloud forms managing it if inside we do that we want to see how that works right we are reshaping documentation console to kind of help you better instead of just documenting features and knobs as in how can how do you want to achieve things now part of this is the configuration that are the big part of the configuration is the voice of the customer to listen to what you say I've been here at Red Hat a few years and one of my passion has always been really hearing from customers how they do it I travel constantly in the world and meet with customers because I want to know what is really going on we use channels like support we use channels like getting from salespeople the interaction from customers we do surveys we do you know we interact with our people to really hear what you do what we also do what maybe not many know and it's also very unique in the industry we have a webpage called you asked reacted we show very transparently you told us this is an area for improvement and it's not just in support it's across the company right build us a better web store build us this we're very transparent about Hades improvements we want to do with you now if you want to be part of the process today go to the feedback zone on the next floor down and talk to my team I might be there as well hit me up we want to hear the feedback this is how we talk about configuration of the organization how we are configured let me go to let me go to another part which is innovation innovation every day and that in my opinion the enable section right we gotta constantly innovate ourselves how do we work with you how do we actually provide better value how do we provide faster responses in support this is what we would I say is is our you know commitment to innovation which is the enabling that Jim talked about and I give you a few examples which I'm really happy and it kind of shows the open source culture at Red Hat our commitment is for innovation I'll give you good example right if you have a few thousand engineers and you empower them you kind of set the business framework as hey this is an area we got to do something you get a lot of good IDs you get a lot of IDs and you got a shape an inter an area that hey this is really something that brings now a few years ago we kind of said or I say is like based on a lot of feedback is we got to get more and more proactive if you customers and so I shaped my team and and I shaped it around how can we be more proactive it started very simple as in like from kbase articles or knowledgebase articles in getting started guys then we started a a tool that we put out called labs you've probably seen them if you're on the technical side really taking small applications out for you to kind of validate is this configured correctly stat configure there was the start then out of that the ideas came and they took different turns and one of the turns that we came out was right at insights that we launched a few years ago and did you see the demo yesterday that in Paul's keynote that they showed how something was broken with one the data centers how it was applied to fix and how has changed this is how innovation really came from the ground up from the support side and turned into something really a being a cornerstone of our strategy and we're keeping it married from the day to day work right you don't want to separate this you want to actually keep that the data that's coming from the support goes in that because that's the power that we saw yesterday in the demo now innovation doesn't stop when you set the challenge so we did the labs we did the insights we just launched a solution engine called solution engine another thing that came out of that challenge is in how do we break complex issues down that it's easier for you to find a solution quicker it's one example but we're also experimenting with AI so insights uses AI as you probably heard yesterday we also use it internally to actually drive faster resolution we did in one case with a a our I bought basically that we get to 25% faster resolution on challenges that you have the beauty for you obviously it's well this is much faster 10% of all our support cases today are supported and assisted by an AI now I'll give you another example of just trying to tell you the innovation that comes out if you configure and enable the team correctly kbase articles are knowledgebase articles we q8 thousands and thousands every year and then I get feedback as and while they're good but they're in English as you can tell my English is perfect so it's not no issue for that but for many of you is maybe like even here even I read it in Japanese so we actually did machine translation because it's too many that we can do manually the using machine translation I can tell it's a funny example two weeks ago I tried it I tried something from English to German I looked at it the German looked really bad I went back but the English was bad so it really translates one to one actually what it does but it's really cool this is innovation that you can apply and the team actually worked on this and really proud on that now the real innovation there is not these tools the real innovation is that you can actually shape it in a way that the innovation comes that you empower the people that's the configure and enable and what I think is all it's important this don't reinvent the plumbing don't start from scratch use systems like containers on open shift to actually build the innovation in a smaller way without reinventing the plumbing you save a lot of issues on security a lot of issues on reinventing the wheel focus on that that's what we do as well if you want to hear more details again go in the second floor now let's talk about the engage that Jim mentioned before what I translate that engage is actually engaging you as a customer towards your success now what does commitment to success really mean and I want to reflect on that on a traditional IT company shows up with you talk the salesperson solution architect works with you consulting implements solution it comes over to support and trust me in a very traditional way the support guy has no clue what actually was sold early on it's what happens right and this is actually I think that red had better that we're not so silent we don't show our internal silos or internal organization that much today we engage in a way it doesn't matter from which team it comes we have a better flow than that you deserve how the sausage is made but we can never forget what was your business objective early on now how is Red Hat different in this and we are very strong in my opinion you might disagree but we are very strong in a virtual accounting right really putting you in the middle and actually having a solution architect work directly with support or consulting involved and driving that together you can also help us in actually really embracing that model if that's also other partners or system integrators integrate put yourself in the middle be around that's how we want to make sure that we don't lose sight of the original business problem trust me reducing the hierarchy or getting rid of hierarchy and bureaucracy goes a long way now this is how we configured this is how we engage and this is how we are committed to your success with that I'm going to introduce you to John Alessio that talks more about some of the innovation done with customers thank you [Music] good morning I'm John Alessio I'm the vice president of Global Services and I'm delighted to be with you here today I'd like to talk to you about a couple of things as it relates to what we've been doing since the last summit in the services organization at the core of everything we did it's very similar to what Marco talked to you about our number one priority is driving our customer success with red hat technology and as you see here on the screen we have a number of different offerings and capabilities all the way from training certification open innovation labs consulting really pairing those capabilities together with what you just heard from Marco in the support or cee organization really that's the journey you all go through from the beginning of discovering what your business challenge is all the way through designing those solutions and deploying them with red hat now the highlight like to highlight a few things of what we've been up to over the last year so if I start with the training and certification team they've been very busy over the last year really updating enhancing our curriculum if you haven't stopped by the booth there's a preview for new capability around our learning community which is a new way of learning and really driving that enable meant in the community because 70% of what you need to know you learned from your peers and so it's a very key part of our learning strategy and in fact we take customer satisfaction with our training and certification business very seriously we survey all of our students coming out of training 93% of our students tell us they're better prepared because of red hat training and certification after Weeds they've completed the course we've updated the courses and we've trained well over a hundred and fifty thousand people over the last two years so it's a very very key part of our strategy and that combined with innovation labs and the consulting operation really drive that overall journey now we've been equally busy in enhancing the system of enablement and support for our business partners another very very key initiative is building out the ecosystem we've enhanced our open platform which is online partner enablement network we've added new capability and in fact much of the training and enablement that we do for our internal consultants our deal is delivered through the open platform now what I'm really impressed with and thankful for our partners is how they are consuming and leveraging this material we train and enable for sales for pre-sales and for delivery and we're up over 70% year in year in our partners that are enabled on RedHat technology let's give our business partners a round of applause now one of our offerings Red Hat open innovation labs I'd like to talk a bit more about and take you through a case study open innovation labs was created two years ago it's really there to help you on your journey in adopting open source technology it's an immersive experience where your team will work side-by-side with Red Hatters to really propel your journey forward in adopting open source technology and in fact we've been very busy since the summit in Boston as you'll see coming up on the screen we've completed dozens of engagements leveraging our methods tools and processes for open innovation labs as you can see we've worked with large and small accounts in fact if you remember summit last year we had a European customer easier AG on stage which was a startup and we worked with them at the very beginning of their business to create capabilities in a very short four-week engagement but over the last year we've also worked with very large customers such as Optim and Delta Airlines here in North America as well as Motability operations in the European arena one of the accounts I want to spend a little bit more time on is Heritage Bank heritage Bank is a community owned bank in Toowoomba Australia their challenge was not just on creating new innovative technology but their challenge was also around cultural transformation how to get people to work together across the silos within their organization we worked with them at all levels of the organization to create a new capability the first engagement went so well that they asked us to come in into a second engagement so I'd like to do now is run a video with Peter lock the chief executive officer of Heritage Bank so he can take you through their experience Heritage Bank is one of the country's oldest financial institutions we have to be smarter we have to be more innovative we have to be more agile we had to change we had to find people to help us make that change the Red Hat lab is the only one that truly helps drive that change with a business problem the change within the team is very visible from the start to now we've gone from being separated to very single goal minded seeing people that I only ever seen before in their cubicles in the room made me smile programmers in their thinking I'm now understanding how the whole process fits together the productivity of IT will change and that is good for our business that's really the value that were looking for the Red Hat innovation labs for us were a really great experience I'm not interested in running an organization I'm interested in making a great organization to say I was pleasantly surprised by it is an understatement I was delighted I love the quote I was delighted makes my heart warm every time I see that video you know since we were at summit for those of you who are with us in Boston some of you went on our hardhat tours we've opened three physical facilities here at Red Hat where we can conduct red head open Innovation Lab engagements Singapore London and Boston were all opened within the last physical year and in fact our site in Boston is paired with our world-class executive briefing center as well so if you haven't been there please do check it out I'd like to now talk to you a bit about a very special engagement that we just recently completed we just recently completed an engagement with UNICEF the United Nations Children's Fund and the the purpose behind this engagement was really to help UNICEF create an open-source platform that marries big data with social good the idea is UNICEF needs to be better prepared to respond to emergency situations and as you can imagine emergency situations are by nature unpredictable you can't really plan for them they can happen anytime anywhere and so we worked with them on a project that we called school mapping and the idea was to provide more insights so that when emergency situations arise UNICEF could do a much better job in helping the children in the region and so we leveraged our Red Hat open innovation lab methods tools processes that you've heard about just like we did at Heritage Bank and the other accounts I mentioned but then we also leveraged Red Hat software technologies so we leveraged OpenShift container platform we leveraged ansible automation we helped the client with a more agile development approach so they could have releases much more frequently and continue to update this over time we created a continuous integration continuous deployment pipeline we worked on containers and container in the application etc with that we've been able to provide a platform that is going to allow for their growth to better respond to these emergency situations let's watch a short video on UNICEF mission of UNICEF innovation is to apply technology to the world's most pressing problems facing children data is changing the landscape of what we do at UNICEF this means that we can figure out what's happening now on the ground who it's happening to and actually respond to it in much more of a real-time manner than we used to be able to do we love working with open source communities because of their commitment that we should be doing good for the world we're actually with red hat building a sandbox where universities or other researchers or data scientists can connect and help us with our work if you want to use data for social good there's so many groups out there that really need your help and there's so many ways to get involved [Music] so let's give a very very warm red hat summit welcome to Erica kochi co-founder of unicef innovation well Erica first of all welcome to Red Hat summit thanks for having me here it's our pleasure and thank you for joining us so Erica I've just talked a bit about kind of what we've been up to and Red Hat services over the last year we talked a bit about our open innovation labs and we did this project the school mapping project together our two teams and I thought the audience might find it interesting from your point of view on why the approach we use in innovation labs was such a good fit for the school mapping project yeah it was a great fit for for two reasons the first is values everything that we do at UNICEF innovation we use open source technology and that's for a couple of reasons because we can take it from one place and very easily move it to other countries around the world we work in 190 countries so that's really important for us not to be able to scale things also because it makes sense we can get we can get more communities involved in this and look not just try to do everything by ourselves but look much open much more openly towards the open source communities out there to help us with our work we can't do it alone yeah and then the second thing is methodology you know the labs are really looking at taking this agile approach to prototyping things trying things failing trying again and that's really necessary when you're developing something new and trying to do something new like mapping every school in the world yeah very challenging work think about it 190 countries Wow and so the open source platform really works well and then the the rapid prototyping was really a good fit so I think the audience might find it interesting on how this application and this platform will help children in Latin America so in a lot of countries in Latin America and many countries throughout the world that UNICEF works in are coming out of either decades of conflict or are are subject to natural disasters and not great infrastructure so it's really important to a for us to know where schools are where communities are well where help is needed what's connected what's not and using a overlay of various sources of data from poverty mapping to satellite imagery to other sources we can really figure out what's happening where resources are where they aren't and so we can plan better to respond to emergencies and to and to really invest in areas that are needed that need that investment excellent excellent it's quite powerful what we were able to do in a relatively short eight or nine week engagement that our two teams did together now many of your colleagues in the audience are using open source today looking to expand their use of open source and I thought you might have some recommendations for them on how they kind of go through that journey and expanding their use of open source since your experience at that yeah for us it was it was very much based on what's this gonna cost we have limited resources and what's how is this gonna spread as quickly as possible mm-hmm and so we really asked ourselves those two questions you know about 10 years ago and what we realized is if we are going to be recommending technologies that governments are going to be using it really needs to be open source they need to have control over it yeah and they need to be working with communities not developing it themselves yeah excellent excellent so I got really inspired with what we were doing here in this project it's one of those you know every customer project is really interesting to me this one kind of pulls a little bit at your heartstrings on what the real impact could be here and so I know some of our colleagues here in the audience may want to get involved how can they get involved well there's many ways to get involved with the other UNICEF or other groups out there you can search for our work on github and there are tasks that you can do right now if and if you're looking for to do she's got work for you and if you want sort of a more a longer engagement or a bigger engagement you can check out our website UNICEF stories org and you can look at the areas you might be interested in and contact us we're always open to collaboration excellent well Erica thank you for being with us here today thank you for the great project we worked on together and have a great summer thank you for being give her a round of applause all right well I hope that's been helpful to you to give you a bit of an update on what we've been focused on in global services the message I'll leave with you is our top priority is customer success as you heard through the story from UNICEF from Heritage Bank and others we can help you innovate where you are today I hope you have a great summit and I'll call out Jim Whitehurst thank you John and thank you Erica that's really an inspiring story we have so many great examples of how individuals and organizations are stepping up to transform in the face of digital disruption I'd like to spend my last few minutes with one real-world example that brings a lot of this together and truly with life-saving impact how many times do you think you can solve a problem which is going to allow a clinician to now save the life I think the challenge all of his physicians are dealing with is data overload I probably look at over 100,000 images in a day and that's just gonna get worse what if it was possible for some computer program to look at these images with them and automatically flag images that might deserve better attention Chris on the surface seems pretty simple but underneath Chris has a lot going on in the past year I've seen Chris Foreman community and a space usually dominated by proprietary software I think Chris can change medicine as we know it today [Music] all right with that I'd like to invite on stage dr. Ellen grant from Boston Children's Hospital dr. grant welcome thank you for being here so dr. grant tell me who is Chris Chris does a lot of work for us and I think Chris is making me or has definitely the potential to make me a better doctor Chris helps us take data from our archives in the hospital and port it to wrap the fastback ends like the mass up and cloud to do rapid data processing and provide it back to me in any format on a desktop an iPad or an iPhone so it it basically brings high-end data analysis right to me at the bedside and that's been a barrier that I struggled with years ago to try to break down so that's where we started with Chris is to to break that barrier between research that occurred on a timeline of days to weeks to months to clinical practice which occurs in the timeline of seconds to minutes well one of things I found really fascinating about this story RedHat in case you can't tell we're really passionate about user driven innovation is this is an example of user driven innovation not directly at a technology company but in medicine excuse me can you tell us just a little bit about the genesis of Chris and how I got started yeah Chris got started when I was running a clinical division and I was very frustrated with not having the latest image analysis tools at my fingertips while I was on clinical practice and I would have to on the research so I could go over and you know do line code and do the data analysis but if I'm always over in clinical I kept forgetting how to do those things and I wanted to have all those innovations that my fingertips and not have to remember all the computer science because I'm a physician not like a better scientist so I wanted to build a platform that gave me easy access to that back-end without having to remember all the details and so that's what Chris does for us is brings allowed me to go into the PAC's grab a dataset send it to a computer and back in to do the analysis and bring it back to me without having to worry about where it was or how it got there that's all involved in the in the platform Chris and why not just go to a vendor and ask them to write a piece of software for you to do that yeah we thought about that and we do a lot of technical innovations and we always work with the experts so we wanted to work with if I'm going to be able to say an optical device I'm going to work with the optical engineers or an EM our system I'm going to work with em our engineers so we wanted to work with people who really knew or the plumbers so to speak of the software in industry so we ended up working with the massive point cloud for the platform and the distributed systems in Red Hat as the infrastructure that's starting to support Chris and that's been actually a really incredible journey for us because medical ready medical softwares not typically been a community process and that's something that working with dan from Red Hat we learned a lot about how to participate in an open community and I think our team has grown a lot as a result of that collaboration and I know you we've talked about in the past that getting this data locked into a proprietary system you may not be able to get out there's a real issue can you talk about the importance of open and how that's worked in the process yeah and I think for the medical community and I find this resonates with other physicians as well too is that it's medical data we want to continue to own and we feel very awkward about giving it to industry so we would rather have our data sitting in an open cloud like the mass open cloud where we can have a data consortium that oversees the data governance so that we're not giving our data way to somebody else but have a platform that we can still keep a control of our own data and I think it's going to be the future because we're running of a space in the hospital we generate so much data and it's just going to get worse as I was mentioning and all the systems run faster we get new devices so the amount of data that we have to filter through is just astronomically increasing so we need to have resources to store and compute on such large databases and so thinking about where this could go I mean this is a classic feels like an open-source project it started really really small with a originally modest set of goals and it's just kind of continue to grow and grow and grow it's a lot like if yes leanest torval Linux would be in 1995 you probably wouldn't think it would be where it is now so if you dream with me a little bit where do you think this could possibly go in the next five years ten years what I hope it'll do is allow us to break down the silos within the hospital because to do the best job at what we physicians do not only do we have to talk and collaborate together as individuals we have to take the data each each community develops and be able to bring it together so in other words I need to be able to bring in information from vital monitors from mr scans from optical devices from genetic tests electronic health record and be able to analyze on all that data combined so ideally this would be a platform that breaks down those information barriers in a hospital and also allows us to collaborate across multiple institutions because many disorders you only see a few in each hospital so we really have to work as teams in the medical community to combine our data together and also I'm hoping that and we even have discussions with people in the developing world because they have systems to generate or to got to create data or say for example an M R system they can't create data but they don't have the resources to analyze on it so this would be a portable for them to participate in this growing data analysis world without having to have the infrastructure there and be a portal into our back-end and we could provide the infrastructure to do the data analysis it really is truly amazing to see how it's just continued to grow and grow and expand it really is it's a phenomenal story thank you so much for being here appreciate it thank you [Applause] I really do love that story it's a great example of user driven innovation you know in a different industry than in technology and you know recognizing that a clinicians need for real-time information is very different than a researchers need you know in projects that can last weeks and months and so rather than trying to get an industry to pivot and change it's a great opportunity to use a user driven approach to directly meet those needs so we still have a long way to go we have two more days of the summit and as I said yesterday you know we're not here to give you all the answers we're here to convene the conversation so I hope you will have an opportunity today and tomorrow to meet some new people to share some ideas we're really really excited about what we can all do when we work together so I hope you found today valuable we still have a lot more happening on the main stage as well this afternoon please join us back for the general session it's a really amazing lineup you'll hear from the women and opensource Award winners you'll also hear more about our collab program which is really cool it's getting middle school girls interested in open sourcing coding and so you'll have an opportunity to see some people involved in that you'll also hear from the open source Story speakers and you'll including in that you will see a demo done by a technologist who happens to be 11 years old so really cool you don't want to miss that so I look forward to seeing you then this afternoon thank you [Applause]