(upbeat music) >> Hey guys and girls. Welcome back to theCUBE's coverage of Coupa Inspire 2022, from the Cosmopolitan, in bustling Las Vegas. Lisa Martin here, and as I mentioned, day two of our coverage and fresh from the main stage, Raja Hammoud joins me, the Executive Vice President of products at Coupa. Raja, welcome back to theCUBE and happy 10th anniversary at Coupa. >> Oh, thank you, thank you, thank you, and welcome back to Inspire. >> Thank you. It's so great- >> We're so happy you're here. >> It's great to be here. So you're just about coming up on your 10 anniversary with Coupa. You showed some great photos of your time there but you've seen, you've lived the evolution that is this rocket ship that's Coupa. >> Raja: It's been incredible journey. I really couldn't believe at first it's been 10. This is the longest I've ever been anywhere. And I honestly feel more refreshed and excited than even when I joined back in the day 10 years ago. And so much has changed, but also so much has not. >> Lisa: Yeah. >> The size of course. We were like 60 people when I joined, the product development team was one person in, in a product, roughly 12 engineers, and fast forward to the scale that's today, it's phenomenal difference. But what has not changed is the, the core values, how, the hustle, how people love working with each other, how we support customers, how we keep stepping up our game how we believe none of us is as smart as all of us, and the community keeps getting stronger and stronger. It's been, it's been really exciting journey. >> The theme of none of us is as smarter as all of us, I'm not sure if I got that right, but the idea is you feel that when you're talking to Coupa partners, I've had the opportunity to talk with Coupa partners and customers and Coupa folks that, that is not just a value statement, people are living that. >> Raja: Yeah. It's, it's everywhere. In the, in the company walls, outside the company walls, you often see product people in different organizations where, they start living in an ivory tower, they think they know everything, I mean, back to what we were discussing earlier about Barbara, when she talked about, get out of your doors, right? A lot of people can tend to do that. We always, from the beginning, believed in the best ideas are out there and you collaborate with each other. And I truly, truly believe that the success that we have achieved today to our community is in a large, large part, because we believed in that. So like on Monday, we hosted, I can't keep track of the number now, so, so many in-parallel Community Advisory Board meetings, and just talking to the products managers and everybody is buzzing with new ideas. And when we go back, there's so much new innovation that has just been co-created here in this conference, and this keeps going on and on and on. >> Lisa: Yeah. I like how you call it, the Community Advisory Board. I'm still used to hearing CAB as Customer Advisory Board, but what Coupa has built, especially with the launch of the Moonshot, the, the community AI, is, is just that. >> Yes. >> It's a very collaborative community. One of the things that's around here, hashtags everywhere, but #United by the Power of Spend. >> Yes. >> What does that mean to you as the EVP of products, and what do you think that means to the community? >> When I think... What we are doing, we're building this platform that is powering all these businesses out there. And the reality of it is you can only, only do so much when you try to do things alone. When we are doing things together, we are way more successful, we are more profitable, we are more sustainable, we are more efficient. And community.ai from a technology standpoint, is making that happen, because what we are doing is taking AI, applying it to all this 3.3 trillion in data, and then bringing back prescriptions that we give back to each and every customer so that everybody can see where they are, how they up their games, and we connect them with other people like them. Now, people love coming to conferences like this, but even in conferences like this, if you think about it, the people you're going to meet, it's, some people are going to do matchmaking but you are also losing an opportunities of meeting the maximum number of people who've done exactly the thing that you did. But when you have the ability to look at all of that data and you can match make people. So we did that already with, for sourcing professionals. So if you are somebody who source a certain category, we can tell somebody else has done something like this in this geography and we offer you to connect to each other. >> Lisa: Wow. >> So this is incredibly powerful way where we are really uniting the whole community by spend, making everybody truly stronger together. >> Lisa: Matchmaker in, in a sense. >> It is matchmaking. >> But it's, but it's- >> It's Spend matchmaking. >> Spend matchmaking, but it's also the opportunity to unite professionals across sourcing, procurement- >> Raja: Yes. >> ... finance, treasury. >> Raja: Yes. >> To your point, and, and Rob said this in his keynote, and he said it here on theCUBE, you know, we've got to break down these silos. >> Raja: Yes. >> People and companies functioning in silos are not going to be successful. >> Raja: Yes. This has been one of the, probably one of the things that we were talking earlier, what has changed, what hasn't. This is one of the fundamental things that has never changed since I've joined. The vision has been very clear. The execution on it, of how we drive successful business spend management program is by breaking down the silos and this idea of sweet synergy, where in product, you start building these capabilities that helps these professionals in the different organizations to actually connect on the touch points, where, where things really matter. >> Lisa: Sweet synergy, was that thing from a concept perspective, did that come from the community, in terms of Coupa going, this is actually what's happening, this synergy across the BSM suite? >> Yes. So in the very beginning, it was early idea. I would say in the first two Inspires that we did, we hadn't given it actually the name itself, and we used to call it unified capabilities, and it started with the first silos we broke down. The first silos we broke down were procurement and AP. And they didn't even used to talk in the same room or even want to care about each other. So we started building so many capabilities that brought these teams together and little by little the community started to feel that and see the value of that. And then the community started to ask us to go break down more silos. So in the beginning, I would say the, the vision before I even joined, the company was on that trajectory. And the early customers saw that and they championed it and then they drove us to do more. So they came to us and said could you please do what you did here in contract? Could you please do what you did here in sourcing? And I was in a meeting last week, a leadership meeting, and one question was asked to leaders in the services team about what are they hearing about, from the customers, about a particular area. And it was music to our ears when we heard the customers are asking for more synergy, right? So, they even have the name for it and they're asking for more and more, and we have built hundreds of these already, but the reality is there is so much opportunity. >> Lisa: Right. >> The world is siloed, no technology has attempted to do that. And I think that's what's a exciting is to go and forge new grounds and do something very special to unite everyone together. >> You guys talked about the waves. Rob talked about the waves yesterday. You talked about it again this morning. And when I think of Inspired community, as that third wave, I see it on both sides. I see the Inspired community that is the Coupa community, but also what you just talked about, that flywheel of that sort of symbiotic relationship that you guys have with your customers as Coupa in and of itself being in a community inspired by the community that it has built. >> Raja: Yes, it's, it's very, very, it's a circular effect. Like it, we inspire one another, and we strengthen one another, and it's, it's just a beautiful, beautiful thing. One of the special things that we are starting to do is we want to take the whole product experience itself, to be a complete community experience. So anywhere you are going to Coupa, when it makes sense, of course, you are not only looking at your data, you are getting connected with people for that particular thing. So we've done that already for 15 different product areas and we're constantly doing more and more and more and more. You can imagine one day we can, where we can start within the product pages themselves, where we host community experts to talk via video and connect with others. So you bring that whole community experience alive in a product in enterprise software, which has not been done. >> Kind of like creating your own influencer network. >> Yes, yes, yes. And give people their voice and, and, and it becomes exciting. It is very different when you're just working on your own and driving goals, and you have no idea how good that can pass on the world. And then when right then and there, you get to learn that some people have hit that, some people have achieved these goals, you just get excited, "I want to hit that goal too. Who are these people? Connect me with these leaders. Let's have a conversation. How did they do it?" And they start creating best practices together. We even have started places where they collaborate on actual documents and templates, and they put them in the community exchange as a way for people to share with others, even taking templates from the product putting them back into a community exchange. So it is sharing, being enabled on the platform, platform itself. >> Lisa: How did you guys function during the pandemic, the last two years when we couldn't get together? >> Raja: Yeah. >> I know that your customers are really the lifeblood of Coupa and vice versa. >> Raja: Yes. >> But talk to me about some of the things that Coupa did with its customers, you know, by video conferencing, for example, that really helped the evolution and some of the innovations that you announced this morning. >> When we first... when the pandemic first hit I think like we all didn't believe what, what is going on. And there was this, I would call it a beautiful period in a way, despite how horrific that was, and that period was where everyone rose to the occasion, everybody wanted to help one another. Across Coupa everywhere, we started having documents of how can step up and help our customers, help our communities. We started to look at how we get PPE, and get it in the hands of our customers. We have access to suppliers. We started looking at helping suppliers with digital payments to speed things up. So, so many things we started doing as a community to just help each other. And then as we got to the next level, then we started, of course, starting to do things over, over zoom. And the big surprise, was we were incredibly productive. If anything, we were worried about people feeling burnt out. >> Yeah. >> Because they were just in it, completely in it. And it created a lot of new avenues for us because often you go and do these meetings in person. Now you could have a user experience session with a customer very easily, they're available more often than they used to. >> Lisa: Right. >> So we did not miss a beat with the community. We moved into virtual caps. We had the advantage of having them recorded as well, where we could have the global development teams learn and see exactly what the, what the customers are are co-creating together. And our goal lives accelerated, because a lot of these implementations, they used to happen in person, so schedules, they actually got accelerated- >> Lisa: Right. >> ...through that. Now of course, there is nothing that matches to this. You can do it, you can do a lot, but a ton of the collaboration comes from real life dialogue and kind of conversation. So it's that balance between the two that I think will be great. >> Lisa: What are some of the things that you've heard the last few days? You mentioned the Partners Summit and, and the Community Advisory Boards on Monday, yesterday, everything kicked off today. What are some of the things that you've heard in your meetings that really inspire you on say the next 10 years at Coupa? >> Raja: By far, by far, by far, it's a validation of, that what we are doing is, we're absolutely on target with it, and that, we just can do so much more. The silos are massive and there are so so many opportunities that you hear in every different areas that we could be doing this, we could be doing this together. So we can break down more and more silos. And using community.ai is just the tip of the iceberg of what we are, what we are doing. Yes, we created tens and tens of capabilities, helping, helping the community with all of that, but data drives everything. And when you look at that, every single process in every single silo can be informed by the power of data within your own company, and then even better, data across. And, and to the point where we're talking about concepts that customers are really excited about, even thinking about this community, they're customers of each other. And when you are a customer of each other what are the different ways as a community, you can help one another more. So we're talking about community netting as new types of concepts. >> Lisa: Talk to me a little about that. You mentioned the community netting this morning but I didn't quite... Help me understand. >> Raja: It is very simple terms is if, if we are buying from each other and we have to do money movements every time I have to pay you, I have to incur fees and likewise, but since we are part of this community we can manage that relationship. So we just pay the Delta, we net it out. So it, it saves reconciliation times it saves money movement. And these are tip of the icebergs of these very cool things that we're doing together. >> Wow. That's fantastic. Last question for you, as you talk with prospects who are in the early stages, or, or still determining, do we go through like a supply chain digital transformation? I mean, I think of companies that probably haven't now or need to get on the bandwagon. >> Raja: Yeah. >> What are some of the things that you advise to those customers to be able to do what Mick Ebeling talked about this morning and that is, commit and then figure it out? >> Raja: Yes. The number one thing is just make sure you don't do the analysis paralysis. There are just so many opportunities so many opportunities start with a project, get going, and it creates incredible momentum, and then you can move on from one to another, to another, to another, instead of trying to just go for a year or two, trying to look at how the world has changed in that process. And so often you could see that projects pay for themselves within the first month of go life. You do that, you'll create another one. And it's not like you are coming in to do something so new nobody has done. Hundreds and hundreds and thousands as a matter of fact, of other community members have done that. It is proven. So get started with those and then continue. Other things I will be talking to them about is to make sure that they understand the way we work is all about partnerships spread. Often people who haven't worked with us in the enterprise software, they're used to working with vendors. We are not that. We never were that. Like the number one, if we're not going to be real partners, honest, transparent and work with each other, we don't waste each other's time. >> Lisa: Well, Raja, it's been great having you on the program. I've really enjoyed your keynote this morning. Congratulations on your 10 years at Coupa. >> Raja: Thank you. >> I'm excited to see what the next 10 years brings for you. We appreciate your insites and everything that Coupa is doing in partnership with its customers is very evident in an event like this. >> Raja: Thank you. And thank you for coming and covering us as well. We really appreciate it. >> Lisa: It's our pleasure to be here. >> Thank you. >> For Raja Hammoud, I'm Lisa Martin. You're watching theCUBE's coverage, day two of Coupa Inspire 2022, from Las Vegas. (upbeat music)

>>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.

>>Hi everyone, This system A fellow from the University of Tokyo before I thought that would like to thank you she and 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 or some of the recent works that have been done either by me or by character of Hong Kong Noise Group indicating the title of my talk is a neuro more fic in silica simulator for the commenters 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 I will show some proof of concept of the game in performance that can be obtained using dissimulation in the second part and the production 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 adapted from a recent natural tronics paper from the Village Back 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 purification machine, or a recently proposed restricted Bozeman machine, FPD eight, 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 influx you beat or the energy efficiency off memory sisters uh P. J. O are still an attractive platform for building large theorizing 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 particle 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 f. D. A s. 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 suggesting 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 neck 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 a 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 Cortes in machine, which is a growing 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 cooking cm using oh, more than detection and refugee A then injection off the cooking time and eso this dynamics in both cases of CME 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 rising 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 convergence to the global minimum of there's even 20 and using this approach. And so this is >>why we propose toe introduce a macro structure the system or where one analog spin or one D o. P. O is replaced by a pair off one and knock spin and one error on cutting. 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 to force the amplitude of the expense toe, become equal to certain target amplitude. A Andi. This is known by moderating the strength off the icing complaints or see the the error variable e I multiply the icing complain here in the dynamics off UH, 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 think introduces a >>symmetry in the system, which in turn creates chaotic dynamics, which I'm showing here for solving certain current size off, um, escape problem, Uh, in which the exiled from here in the i r. From here and the value of the icing energy is shown in the bottom plots. And you see this Celtics search that visit various local minima of the as Newtonian and eventually finds the local minima Um, >>it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing hamiltonian 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 the limits of contractors or quality contractors. They can also be destabilized using a moderation of the target amplitude. And so we have proposed in the past two different motivation of the target constitute the first one is a moderation that ensure the 100 >>reproduction rate of the system to become positive on this forbids the creation of any non tree retractors. And but in this work I will talk about another modulation or Uresti 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 the current 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 eso 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 everything. Yet for a system with 500 spins analog 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 tobacco cm 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 gear repression to replicate the post phaser 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, all the dog products, respect to the problem size. And and if we had a new infinite amount of resources and PGA to simulate the dynamics, then the non in optical 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 low carrot off end and while the kite off end. Because computing the dot product involves the summing, all the terms in the products, which is done by a nephew, Jay by another tree, which heights scares a 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 and over you and for the products in the end of you square eso typically for low NF pdf cheap P a. You know 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 started 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 Yeah, click the extra co components within the F p G A in order which is shown here in this right panel here in order to minimize the finding finance of the system and to minimize the long distance that the path in the in the fpt So I'm not going to the details of how this is implemented the PGA. But just to give you a new idea off why the Iraqi Yahiko organization off the system becomes extremely important toe get good performance for simulator organizing mission. 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 result for solving escape problems, free connected person, randomly person minus one, spin 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 Nina successful BT against the problem size here and and in red here there's propose F B J 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. It's similar to the car testing machine >>and security. You see that the scaling off the numbers of metrics victor 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 is possibility 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 center dining in purple, for example, and So you see that the scaring off this purpose simulator is is rather good and that for larger politicizes, we can get orders of magnitude faster than the state of the other approaches. >>Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FBT implementation would be faster than risk Other recently proposed izing machine, such as the Hope you know network implemented on Memory Sisters. 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 implemented a PGA proposed by some group in Brooklyn recently again, which is very fast for small promise sizes. But which canning is bad So that, uh, this worse than the purpose approach so that we can expect that for promise sizes larger than, let's say, 1000 spins. The purpose, 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 cut values 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 recount. 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 trickle 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 problems respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital and, you know, free to is shown in the green here, the green >>line without that's and, uh and we should two different, uh, prosthesis 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 showed that we probably can solve Prime Escape Program of Science 2000 spins 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 or 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 out 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 classical 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 eight f p g. A. In which we will add the more refined models truncated bigger in the bottom question model that just talked about on the supports in which he valued waits for the rising problems and support the cement. So we will announce >>later when this is available, and Farah is working hard to get the first version available sometime in September. Thank you all, and we'll be happy to answer any questions that you have.

(upbeat music) >> Narrator: From around the globe, it's theCUBE with digital coverage of PegaWorld Inspire brought to you by Pegasystems. Everybody welcome back to PegaWorld Inspired 2020 this is theCUBE and I'm Dave Vellante, we're here with Adam Field who is the head of innovation and experience at Pegasystems. Adam thanks for coming on, how are you doing man? >> It's my pleasure Dave, I'm doing well how are you? >> Good thank you, I'm excited we're talking innovation, we're talking to innovation hub but to start with your role I love the title, what do you do? Give us the background story. >> Yeah I get that question quite a bit so, I've been with Pega a little over 15 years now and I've held many roles, but currently as head of innovation and experience we have a team I like to call them Creative Misfits, if you will, we sort of bridge that gap between technology and creative, we do research on emerging tech and try to understand how our clients might use it, how it's going to change the future of work, that's the innovation side, on the experience side, we do things like for these PegaWorld events, we match we where art meets tech and we build these experiential things that people come and see at our events, we build all the demos and all the production that you see on the main stage, so we kind of touch a lot of different things around the future of where technology is going. >> Well, I can see, obviously you're innovative, you've got the awesome set up there, the great mic and sound, (laughing) fantastic you look good So and now you've been involved in previous PegaWorld both from behind the scenes and out front speaking obviously this is completely different, how did you prep differently for PegaWorld 2020 virtual versus what you normally do? >> Yeah right so this will be my well 16th I guess PegaWorld and obviously this one stands out as the most different normally we'd be in Boston today, we would have been, you know, working on our stage production and on a floor that's 170,000 square feet big with dozens of booths and hundreds of demos, and obviously this was completely different, but as far as prep goes, I remember the day we learned that early March, this was going virtual and after a few moments of sadness, the team really came together, and I remember the first thing we talked about is we're not going to take a three day event and try to put it all online. Let's--we know people's time is valuable, let's figure out how to take just what's important and get it out to people so that they're inspired to move forward and engage with Pega, so I think that's really been the biggest change in how we've prepped. >> Well, I think that's a great point because obviously theCUBE has been very much involved in these virtual events and. >> Right. >> People send out the note, hey we've made the tough decision to go virtual that's easy decision you really had no choice. >> That's right. >> The tough decision is what do you want to preserve from the physical and understanding that you can't just pop physical into virtual and you got to create a whole new content program, I think Robert Scoble wrote a post on, if you saw it he talks about, hey you better go out and hire Beyonce, oh you can't afford to be for Beyonce? well you better make your content interesting. So to me Adam, that's the tough part, help us understand how you thought that through and what the outcome actually is. >> Yeah, that's right. We didn't have Beyonce, but we did have the Dropkick Murphys, so that was pretty cool and they did a concert for us, so that's been great. But again a lot of people talk about all this free time that they have and I know I have two young kids who are schooling at home now, a job that's busier than it's ever been. I've tried to join a lot of these virtual events and frankly I have gotten overwhelmed, so we took two days and we boiled it down in a two and a half hours, and what we decided to do is we looked at all the areas which we go to market and how people design and deliver their apps, and some of the tech like Pega cloud that they use. And we went to our, I went to my extended team and I said, normally you have 75 booths, we're going to boil that down to 25, let's work together to figure that out. Normally your demos might be 20 minutes when someone walks up, we want to make them seven. But I think the biggest thing that we did, we said what we don't want to lose is that interactivity, and so we had online dozens of Pega experts we could ask questions live, Alan was online doing answering questions live. We made sure that we included live components, our host, Don Sherman was live from his house. We didn't just pre-record everything because then, why would anyone come join when they could just go watch it, 30 minutes later on your YouTube channel? >> See that's innovation to me is having that combination of live. Obviously, you've got to do some stuff a prerecorded, but having a live component adds a dimension, it's challenging, but that's pushing the envelope and I love it. The other thing is, Adam is roles. The roles are different in a virtual event, are they? You're not doing site inspections Like you said, you're not dealing with 170,000 square feet. How did you guys rethink the roles for virtual? >> Yeah so, there were some teams whose world was completely upended. You know, when this all went virtual, the people that do exactly what you were just talking about, dealing with hotels and vendors and things like that, and I got to tell you, one of the most events called PegaWorld Inspire and not to sound too cheesy about it, but one of the things that was really inspiring was to see how everyone stepped up and said, truly, how can I help? And what was really neat about it is we saw different skill sets come out of people that, maybe they hadn't had the opportunity to flex before where they might've worked on one thing that was no longer needed because of the change in the format, and they jumped into become copywriters or liaisons between cause now we have new vendors in this tech world that we didn't have that we turned around in just a matter of weeks. We had people like on my team who normally last year, build this massive physical exhibit containing mirrors and lights, that became video producers, to produce some of these live videos that we did. And one of the things was really impressive, you asked earlier about how did we prep differently and what changed? We looked in the marketplace for different tech and how to bring our CEO and our host and our head of product and everyone together live in split screen, and when you're a big studio you know, and you have that equipment ready to go, that's easy, but when you're just getting average people in their homes and you want to put all that together, we're finding some of the tech in the marketplace just wasn't there. My team built some new video chat technologies that they actually use to produce this in real time, so that was really impressive to me how we turn that around and really innovated not only the things that everyone sees, but all the stuff behind the scenes to. >> See again I think this is what's amazing to me is as I learned more and more about Pega interview Alan earlier. >> Sure. >> Pega is all about being able to adapt to these changes. So a lot of the processes we are using in virtual events, they're unknown. In normally software right through the history of software is okay, here's how the software works. Figure out how to fit your process into it, very rigid. >> That's right. >> Today you know, the last three months with this lockdown in this coronavirus have been completely unknown, and so that's sort of one of the hallmarks of your company, isn't it? >> That's right and we've had the tagline Build For Change for really long time, and I will tell you, I remember in that first meeting again, when we learned this was going virtual and someone stood up and they said, guys we're about to live our tagline. And people really do believe in that, 'cause we go to our clients every single day and say, change is what's going to make you special changes is what's going to make you different, now's your opportunity, seize that change and run with it. And so we said, look, we can't change the world right now, we know we got to go virtual, all we can do is change the type of event that we do, we're not going to do the standard event that we think every one else is going to do, let's do it differently and today was a pretty good example, I think we achieved that. >> I think a couple of things from a challenge standpoint, you mentioned the chat, how do you get people to engage? You had to sort of invent something. >> Yeah. >> And then really think it through for virtual. And I think the other is tech people come to these events, they want to touch the tech. And so you've got you know the innovation hub, it's where people get to play with the technology. You got to take us through how you thought through that and. >> Right. >> What the outcome is. >> Yeah, so that is the toughest part, and I got to tell you, you know all of this being said, I'm looking forward to someday being able to get back and meeting my clients in person, and I'm the type, when I see you on the floor of the innovation hub, I run by a booth and high five you for all the great weeks of hard work, you know? And I love to see people's faces, they see the demos and that's tough not being able to see them smile and get that moment of wow. But what was interesting was it really helped us hone our messages. I think we really realized when I went to everybody and said you don't have 20 minutes, you have seven minutes, here's a template, to follow, to be able to tell your story better, and people started thinking in that mode of storytelling, and what was interesting was lot of people came back to me and said, actually you know what? I can tell that story in a much more crisp way and really show people what they need to see in a in a much faster timeframe. And what it really allowed us to do was find those bits that we thought were most important, find those demos that we think are most important and just, you know bubble those up. One of the things we also did too, we took the opportunity to say you know what, we're going to be online, I watch my kids. My kids are avid gamers whether I like it or not, and they. >> Yeah. >> Watch these Twitch streams, and we thought well, we should be able to do that with even corporate software. So we had these live build sessions where we took some of our developers and I said you're going to be put on the hot seat for 15 minutes on script and we're going to let people just guide and direct you. And they were a little nervous at first, but they went off great, and it was a new format we had never tried before. So if we keep doing these types of different things and we just embrace the moment that we're in I think people will really really come to it and get some value out of it. >> I mean that's awesome, you've got to keep your audience engaged, and so you do lose, you don't have a captive audience, so you lose some time in terms of how much you can you know? how much Kool-Aid injection you can give him. I mean take 20 minutes down to seven minutes. But so you do lose some of that, but what do you gain with virtual? >> Well, I think one of the things that you obviously gain is you can be more widespread, so yeah, you know this event reached tens of thousands of people in dozens of countries. I did an event first week of April, so you can imagine you know, we had two weeks to turn on and I was supposed to be in London and Amsterdam presenting in soccer stadiums. And instead we made that a one hour virtual event and we thought, well, we're just going to get people from the London market and from the Netherlands market, and it turned out, we got people from all over the world to join. So one of the benefits to this is the reach, so we're able to reach a lot more people. I'd say one of the other just things that we realized after tours we're creating a lot of content, we filmed all of this as we were rehearsing, and we're going to put it up online later, so now we have all this great content that anyone can use and go view later, so that was sort of you know, unexpected outcome as well. >> Right yeah, you lose the airline miles, but you gain. (laughing) as I want to going to say you gian the post. >> I don't mind not traveling as well. >> Yeah I here you but, but you do gain that post and I think with physical events, people always at the end of it, it's like, I've never given birth, but I've witnessed that many times. but people feel like, okay, I got to just chill out now for a couple of weeks, and then when they come back, now they're swamped, they've got to catch up. And I think people are realizing, wow, there's a real opportunity maximize the post event here, post nurturing peep streaming out content and continue that engagement, that is a plus of these virtual event. >> Oh, for sure, and you know we started early on deciding how are we going to do, what are we going to do is follow ups you know? That European event that I talked about once again instead of taking all these different markets and trying to replicate it, we did one one hour event. But then because we were in the early days of COVID and some of our clients weren't able to get recorded and speak, we did subsequent webinars in the weeks following them, and the attendance was fantastic. So it allowed us to plan ahead and you know, have a lot of followup activities that we're starting to launch right now as soon as the event ended. >> How do you feel about the outcome for Pega? Do you think it was better, worse, the same or just different? >> I'm going to go with different you know, like I said I get energy I love being up on stage in front of 5,000 people, I love meeting my clients in person, I love the energy of being with my colleagues, but you know it is what it is, We had to do it, and I think what we really embraced it, so I'll say it's just a different way of doing things, but you know I do look forward to the day that I'm able to go meet my clients again and get back on stage and produce some really great things and once again being able to physically see our attendees go oh, when they actually see the software in person, that's the most rewarding thing for me. >> It's going to be interesting as we come out of this I mean, very clearly things are going to be different probably going to have hybrid for some time. Maybe even indefinitely but I'm interested in some of the learnings, some of the things that you think will be permanent, some of the advice. And one of the things I always say to people is don't start with what software are we going to use in there? Your software platform, think about the experience that you want to work backwards from there but what are other advice would you give for given your experiences? >> Right. >> You're so right about that point, I remember interviewing a lot of vendors that we were going to use to bring this online and we were telling them what we wanted to do, and some of them said no one's ever asked about that before we can't do that, so you're a hundred percent right about that. The advice I will say, and the thing I do worry about a little bit is, at first people were a little bit more accepting if maybe the video quality wasn't as good, or you know the content was like any old webinar. As months ago on expectations are going to be higher, people are going to have attended a lot of these things so you're going to have to keep upping the game. And I think the advice I would give is try to take what's great about an in person event and put it online but don't try to replicate the event and put it online. And some of the best things about in person events are just the live nature of it, take the risks, do some live stuff. People will really appreciate that, you'll get a lot of credit for that. The interactivity is what's important about a live event, so as best you can, figure out how to make sure there's some interactivity. Now in the early days I think it's going to be some live Q and A as we move on, it'll be real private rooms with experts that you're able to have one-on-one chats and go through and bounce around and be able to talk to people you know, just like you would accept, between two cameras instead of in person. So I think everyone is months go on. they just going to have to up their game. I think that's great advice, you're absolutely right up your game, up your brand, get a good camera, get good sound, and it's going to just, help your personal brand and your company's brand. Adam. >> We learned what it was like to try to ship microphone and camera equipment around the world (laughing) overnight so we're experts at that, if you you've got any questions. >> Well, I mean what a difference it made, so Adam, thanks so much for coming on theCUBE and sharing your experiences. You guys, have one of the best that we've seen at the Virtual Event Platform so congratulations on that and really appreciate your contribution (mumbles). >> Thanks it's my pleasure, great to talk to you today (mumbles). All right, keep it right there buddy, this is theCUBES coverage of PegaWorld Inspire 2020 the virtual event, will be right back after a short break. (upbeat music)

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. Brought to You by Cooper. >> Welcome to the Cube. Lisa Martin on the ground at Koopa Inspired 19 from Las Vegas. Very excited to welcome one of Cooper's spend centers from the USO acquaintance, senior director of procurement and contract management. Hey, welcome. >> Thank you. I'm glad to be here. >> Yeah, so this is one of the things that I really appreciate it with. All of the tech conference is that we go to on the Q, which is many, Many a year is when vendors like Cooper really share their success is through the voices and the stories of their successful customers. You got called out yesterday during general session today. There's a big cardboard cutout of you behind us there. But one of the things also that I find intriguing is looking at older organizations, and USO is 77 years young. We think of older organizations challenging Thio maneuver that in this digital era and really be able to transform the business so that you could d'oh, what the mission of the U. S. It was, which is to help men and women in our U. S. Armed forces from the time that they enter to the time that they transition back to civilian life. Talked a little bit about us. So what your role is in for cumin and then we'll talk about how you're achieving these great things. >> Well, I've been with us for four years, almost four years. When I first interviewed for this position with my boss, the VP controller, I asked her if they had a secure to pay solution. She said No again when I was hired for this position, My, you know, my goal was to get the organization automated. They were processing everything by paper. All the requisitioning was being processed by paper. It would take for seven seven 10 days. It's for a requisition to be approved because it would literally be something printed out and move from desk to desk, desk on approvals and on the back end for invoicing would occur the same filling out a cover sheet. Everything was printed out, processed manually, so that was kind of my first project when I started and my position was new, procurement had been under the director of canning operation. So, um came. It was just a small piece of it. So they made a decision After he left to create my position on DSO I. Again. That was my goal initially when I started. So So it was going through an R P process, looking, looking our requirements and then selecting vendor gets the best value to the USO, which was Coop up. And Cooper is what I think we all love about. It is it's so customizable, and the USO has a lot of, ah, a lot of different requirements in our barbecue elements. From, you know, we've entertainment tours to our programs, care packages we send out to the military. Our operations are USO Center's construction projects, our development campaigns for on line and direct mail. So there are a lot of different requirements. I really work with each department and kind of setting up those requirements, and Cooper was able to do that for us. We were able to customize a lot of it, But for us, the innovation part is really thinking outside the box because >> tough to do 77 year old organization, right, especially one that has paper everywhere. You guys air now 90.4% paper. Yes, with Cooper, that's a massive Yes, it's cultural change. It's a >> huge and it took again. Another thing. When I interviewed Waas, I interviewed with the CFO as well and I said If you don't support me, I will not be successful. So they have been very supportive. My supervisor, the CFO, the entire organization CEO. It's been extreme. He loves Cooper, so loves the app in improving a breathing invoices requisitions. So it was really that that communication, the socialization training because it was a huge cultural shift and some were embraced it. It was a little tougher for others moving. But eventually you move in line because that is, you know, that's the new process for us as an organization. So it's it's become very successful. We're moving towards new modules contracts, Clm expends sourcing. So we're really expanding the group A picture at us. Oh, >> so what would you say before you came on board when there was so much paper floating around everywhere? You can imagine the security risk of all these, you know, personal information or what have you lying around on someone's desk? What waas The percent, if you could guess visibility into where the U. S. I was spending money prior to bringing on Cooper versus what is it today? >> Uh, extremely small percentage would have been a very small. I mean, we just had a you know, we operate on our European system. Is Great Plains pretty clunky? Not, You know, it's It's hard to see the visibility. Now. It's 100% visibility. We see all of all of the requisitioning occurring overseas. You know, we have centers all over the world, and they all have access to Cooper now because they have to submit requisitions through Cooper. And so we now have 100% visibility. And for our reporting, you know, able to pull all that information and we've got controls in place gave us the ability to put some controls in place and our approval work flows and making sure that contracts were reviewed before budgets air approved, etcetera. A lot of those things were able to set those controls in place in >> that control. Word that you bring up is spot on. We've been talking about that for the last couple of days, and it's the same when we were talking with Suzie Orman earlier, who was one of the key nodes. And when she talks about personal finance, it's sort of the same thing. We all as individuals, whether we're consumers, you know, in our personal lives, buying whenever we want from anything dot com to being buyers or managers of even lines of business. Within whatever company we work for. We need to have that picture that control and control is really that kind of accountability and that awareness. Are we managing everything appropriately? Are there other parts of the business that are doing the same thing that there may be getting the same service is at a better price, and we're we should know that right, but without having that visibility will be able to control of this process is it's an inhibitor to any business being able to transform digitally and be competitive and right to really get back to your core >> mission. Exactly. And that's what's helping you know us with the control way are a 501 c three. So we need tohave that visibility on dhe. Make sure that our donor dollars are being spent wisely, and this enabled enables us to do that enables toe have that that total visibility and making sure those controls are in place. >> Actually, speaking of donor dollars, has this actually been a facilitator of actually being able to increase donations? Because the donors now have this much easier transaction process that can imagine that would be a positive impact there. >> Well, I mean that this is more for our procurements. Mean, Coop is kind of more for our actual procurement. What it does do is it does create process savings and avoidance savings, which we can reinvest in, you know, in our program. Right. So that's where we're seeing it. That's where Steve always seeing it. We've communicated that to him, and then we're also able to provide arse CFO with reporting tools. So we create. We pull all this information from Cooper through reports, and there were able to create a spreadsheet, and he can see how we spend is an organization. You know how we spend in commodities, How where are unbudgeted, you know, kind of get a total of much I budgeted we have for for a specific period of time. So we're able to see all this kind of information. He conceal this in kind of information on one spreadsheet that we created through all the reports that way >> in Crete. >> So I want to get your perspectives on the changing role of the chief procurement officer and the chief financial officer. You know, now they have the opportunity to leverage technology, emerging technologies like artificial intelligence and machine learning to be able to get that visibility and that control, but also be former strategic and really drive top line bought online for their business. Your perspective on this the last few years alone and how were you able to help a 77 year old organization like us so embraced the opportunities that these emerging technologies can deliver? >> Well, I think one key is as because our our organization is all over the world. And then there are centers that could be, you know, roll. And they, you know, they it's the whole vendor presence and the amount of vendors that we as an organization, do bring on. And some of them it's totally understandable where some of them they do need to bring on based on, you know, their availability. But what I'm trying to do, what Cooper has helped me try to do with Cooper advantages to try to leverage our volume organizational volume that was not occurring previously. I think people were just, you know, when the new defender they brought it on because we have a lot of events, you know, supplies for the centers, et cetera. So really trying to, strategically, as an organization to be able to work with the region's on where can we find synergies to kind of consolidating leverage our values for Henderson with Cooper work, we've been able to do that. We can see the span where it's occurring, kind of all the duplications that are occurring. So that's where I'm seeing a bit opportunity and trying to work. >> One of the coolest things about what you guys are doing in procurement with Cooper is this is affecting human lives. Give us a little bit of an overview of what you guys were able to facilitate with Hurricane hearty. Wish struck Houston just about two years ago. I loved that story that >> those kind of those spur of the moment emergency type requisitions that we get and were able to those get processed a lot quicker when when we have group as opposed to previously the way they had processed. It was very labor intensive manually, verbally instead of being able to see it in. You know what's great about the requisitioning piece of it is the comments kind of audit that people can see in all the conversations. So those types of requests that are considered emergencies, they can go a lot sooner on so we can get those service's or the goods out to to that particular project. So that's what we're able to do with that. That particular one is well, being able to support the National Guard and during the Hurricane Harvey >> and accelerate things that really based on the data that you can see, I really need to have acceleration on all the action. >> I mean distant just to our programs team. They support the care packages that we send to the military. Now that we have coop in place, we use 1/3 party fulfillment center. When they receive the product, the receipts are automatically fed into Cooper and applied against the purchase orders, and then they're approved a lot quicker, So then they can receive kicked, tip the product and ship it out overseas because we get. These are based on requests. The military bases have requested to have this particular product being sent over. So this turns the process is cut in half to get the care packages out to the millet. >> That's awesome. Getting care packages to the troops 50% Bastard is outstanding. Last question for you, Rick. Some of the things that Cooper has announced in the last day and 1/2 what excites you about the direction that this company is going in >> for me? The constant changing, I mean, and I was not in the military, so I'm way moved around a lot. I was when I was growing up. I adopt to change a very quickly, but understands some people don't write quickly, but it's bettering themselves, finding the operative, listening to the customer and really making those enhancements based on customer feedback. And I think it helps with the community intelligence that we talk with, you know, with the communities and find out. What are you doing? How how are you doing this? Because a lot of companies will say, Well, I have specific requirements and a lot of them are pretty similar. If people talk, you know, community talks. So that's kind of that's I like getting together and again meeting other, you know, people, customers. And so it's Yeah, it's pretty exciting. >> I like what? How tender this morning, you know, showed the word community and said, Really, it's communication and unity, and you just articulated that beautifully. Listen to the customers. Get the synergies from them. That's why we should. Any software business should be developing right soccer. So thank you so much for joining me on the Cube today, sharing the big impact that you guys are making at the USO charity. Near and dear to my heart. We appreciate your time. >> Thank you very much >> for your acquaintance. I'm Lisa Martin. You're watching the Cube from Cooper inspired 19. Thanks for watching.

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired. 2019. Brought to you by Cooper. >> Welcome to the Cube. Lisa Martin on the ground at Cooper Inspire 19 at the Cosmopolitan, the chic Cosmopolitan in Las Vegas. Very pleased to be joined by my friend David Chang, the VP of business from Hello. Sign a drop box company. David, Welcome to the Cube. >> Thank you for having me on. >> Great to have you here. It is a lot of fun. You could really geek out talking technology all day >> too much. So, >> yeah, there's that >> play that you gotta gamble. It'll keep it real. >> You know, I have no skills in that whatsoever, but maybe I'll try it. I'll take your advice. Give her audience an overview of Hello. Sign. Sure. Drop box Company. What? You guys are what you do. All that good stuff. >> Great. Great. So hello. Sign is today one of the fastest growing, if not the fastest growing electronic signature company in market place today and today we host, I think, over 100,000 paying businesses that use one of our products and over 150 different countries. today we actually were acquired by Dropbox. Sure, everybody's familiar Dropbox or one of the biggest brands in the Internet industry today by the leader in consumer and business files Thinking chair. So John Box actually purchased this, you know, for a number of reasons. First of all, even amazing product and cultural fit with them. But also, Electronic Signature Day is an enormous market. It is one piece of the overall digital transformation, but Elektronik, six year alone, analysts view, is probably a $25,000,000,000 industry, which we've only barely scratched the surface. So it's a huge opportunity, absolutely, and it's that big. That's exactly the you know. That's actually what's shocking about how big it is, because if you think about almost in every business, there are not just one, but probably dozens of different use cases where you need to sign documents. So electronic signature honestly is relevant for everything from all your sales agreements to all of your HR and offer letter and on boarding agreement. It's relevant specifically for all of your procurement and buying agreements, all your vendors contracts that need to be signed, your supply agreements that needs to be signed and D A s o purchase orders. All these documents need to be signed. And today you know, only a few of these use cases have been brought into the digital arena. So there's a whole huge area to grow. And with Dropbox being a leader and content management, where you normally store your documents, >> right, it's >> a natural workflow extension two haven't signed by. Hello, son. >> Excellent. Well, one of the things that we've been talking a lot about we talk about this in every show is the effects of consumer is Asian. And we talked about this yesterday with Rob Bernstein, Cooper's CEO in a number of gas yesterday and today is that we're consumers every day, even when we're at work. Oh, I forgot. I gotta buy this when we go on Amazon, we know we could get it in a day, but now we have the same expectations whether we're buying business, you know, software or what not? And we also want to be able to do things from our mobile phone, including sign. Hey, I got this new job offer or whatever happens to be without having out. Oh my God, there's a pdf. I have to go home, get to my desktop, talk to me about PDS because I can imagine when people either fill them out manually, then they scanning back in and somebody's gotta print it out or fax it. That date is stuck in Pdf. How does hello sign work to free dot data in a Pierre? >> Sure, our design philosophy really is about, you know, make making a superior user experience both for the person who needs to get a document, a document side, but also somebody who's actually gonna be signing it. So when we designed our products, you might as easy as possible for user's to sign that and recognizing some of the difficulties with P D EFS and signing on your mobile phone. We've made our products specifically Mobley responsive, so they don't have to pension, screen, pension, pension scan and all that kind of stuff and typing data. We make it very easy walking through the data entry process to streamline the whole process. We just want to make user customer satisfaction first and foremost >> moving the friction, probably getting documents signed much faster. >> Absolutely. I mean the base, you know, benefits associated the signature. Overall you know, our honestly getting your documents signed significantly faster and more efficiently. We have customers that used to take up to two weeks to get a contract signed. And, you know, as a salesperson, that gets your real nervous, right? So we've seen those contracts now get signed in less than a day. Also, Elektronik senator provides a tonic transparency. So throughout the process, we can actually provide notifications that let the sales people know that somebody's opened up the the >> end. Lt >> looked at the document, reviewed it, signed it, completed it. And even if the document has been signed, the consent of reminders to make sure to sign it. And the third thing is, you know you can't can't emphasize this enough. The value associate with productivity increases. Come on. Everyone's gone out. Printed out the document, walked it over to the scanning machine, you know, then uploading it back in your computer, you know that that whole step, you know, should be completely digital and automated as >> much as >> possible. So we see productivity increases to some of our customers between two x three x for X right in the number in reducing the number of man hours people have to spend to get >> documents only. Is that a cost savings? But all of the you can think of all the other benefits like we're talking about, even for the procurement officers were talking about it at Kuba inspires. It's not just saving money. It's all of the other ripple effects that cost savings, resource, reallocations, speed. All enable this digital transformation, which then enables the business Thio capture new customers. Increased customer, lifetime value, shareholder value. There's a lot of upside to this, >> especially for a company like Cooper. First of all, it's an incredible fit for what we do. Procurement documents. That whole host, um, they need to be signed but by, you know, utilizing Hello, son. We really facilitate that whole experience, and we're very excited to expand our partnership today. We're Cooper Advantage partner. >> Tell me about the Cooper Advantage program benefits. Who wins your >> coop? Advantage is this very unique marketplace that Cooper's brought together. They're pulling together both their customers, some of their lead customers and their matching them with some of the suppliers selected suppliers that provide their customers. Ah, whole host of service is that they need so it could be everything from goods and office supplies. All the way to service is like travel service is, and staffing service is all the way to software key software that their customers would utilize in conjunction with their procurement business. Spend management So companies like close on. So by matchmaking it for the suppliers, they get some pre negotiated discounts that offer them immediate savings off of buying direct from retail and then from ah, supplier side. We get huge benefits because we get to meet some of the most targeted companies that we want. So Cooper effectively is one of our favorite matchmakers. >> Nice. So, yeah, there's a tremendous amount of suppliers in their program. I forget the number and I don't want to misquote it. But I can imagine Cooper customer that's using them for procurement and expenses and invoices and payments. I talked a lot about Cooper pains of new things today. Well, then have the opportunity through the Cooper Advantage program to do prick human contract Scorpios with Hello sign as the e signature. >> Exactly, really, exactly. And that that is, like I said, a great match for what their customers need and by being virtue of a coupe advantage part. Sorry. Keep advantage Supplier. We've been pre vetted by Cooper have also worked out some special pre negotiated discounts with Cooper to make sure we passed that value on to their customers. >> So some of the things that came out today regarding yesterday as well with the Amazon extension you and I talked about the consumer ization affect a few minutes ago. What opportunities is that? Open up to Hello, sign for Cooper paid to be able to enable I t folks to have this visibility for the entire software from search to management. With this consume arised approach, open up doors for Hello Sign. >> Well, I think you know, if you look at the total life cycle of any purchase right from from beginning to end from everything from identifying the products that you want to being able to, you know, negotiate and secure a price that is good for you, you know that whole process. There's always tradition, but a lot of friction there. So the same way that there's friction on the e commerce side, we'll check out and purchase right and getting lining up your payment and Internet payment information Cooper. Streamlining that whole thing for the customer so long without sod is if there's documents they're associated with that with that workflow than by using companies like Hello Sign and our products were able to continue that process of digital izing the end and purchase cycle. >> And I imagine, from an information security perspective, everything >> Come on the old >> days usedto signed >> a contract and I thought, Oh, my boss's desk, Anybody could come by and pick that up So nowadays we you know nowadays we keep it stored securely in the cloud. We have some of the highest security requirements of any signature company out there, and that really matches Cupid's philosophy as well. They go overboard on security, which we really appreciate. That mission is completely lard with each other. >> Awesome. So last few seconds here. I know that you guys are early in the acquisition with Dropbox. What's exciting You for the rest of the calendar. 19. Since all these fiscal years are different. And what's next with you guys in Cuba? Yeah, >> So first of all, with Dropbox, we're just excited to be part of an enormous community of over 500,000,000 users globally So it's It's It's the reach is insane. >> I know >> my mom. Yeah, I think everybody has a DROPBOX account on >> eso getting introduced to their segments, whether it's a consumer segment, SMB and increasingly, the business segment offers huge brand recognition and the potential for new customers with Dropbox. So there's a great synergy from a go to market perspective, and with Cooper, we're very excited about the next stage of our partnership is entering the Cooper Link program. So, uh, you know said Now Cooper customers will be able to sign and send for signature from within the Cooper clr module. Eso any of their contracts vendor agreements that are stored within Cooper without ever having to leave Cooper. You consent for signature and seek the document back. And for a company like Cooper, this is a great strategic value. A because of the benefit it brings its customers, but also with all the great features that Cooper's coming out with leading edge. They want to keep a cz much of that procurement experience from within Cooper. They want Cooper to be that system of record per se and system of transaction for all your business. Ben Management So now you don't have to leave Cooper to perform to get your contract signed. You can do it from all within one place within Cooper, and we enable that. >> That's awesome. That's that's what we want. Keep him. In the experience of that, they actually adopted. They get it done. They're more efficient and and and well, David, it's been such a pleasure to >> have you on >> the Cube. Thank you for joining me today. >> Thanks, Lisa. >> All right, we'll see you next. Time for David Chang. I'm Lisa Martin. You're watching the Cube from Cooper Inspired 19. Thanks for watching.

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. >> Brought to You by Cooper. >> Welcome to the Cube from Cooper inspired 99 Lisa Martin in The Cosmopolitan of Las Vegas. And guess who I have with me from the main stage CEO. Rob Bernstein. Welcome to the Cube. >> You so much. Thank you for having me >> exciting start today. One of Inspire really enjoyed the general session this morning. I learned three things more than three, but there's three that really stick out. One. You like pizza >> I do >> to you like kittens and kittens. And three, since 2016 there has been a five X increase and the spend going through the coop a platform with rocket ship. >> That's right. Huge momentum were well over 1.2 trillion dollars and spend that's gone through the platform. It's accelerating, and our customers are getting a lot of value and visualizing that spending, routing it to prefer contract saving money doing in smart, compliant ways. It's a really exciting time for us. >> It is, and this is across every industry manufacturing, healthcare, retail, et cetera. Every industry has the opportunity to leverage this wealth of data absolute. Cooper has to be able to get that visibility and control of all their spent. That's really revolutionary for any business. >> Well, we're really excited about it. Our community of customers is very excited about it, where building something very special here. I'll tell you one of the most exciting things. When you see that data being used in a way that drives intelligence for each individual customers, you know, we're helping them understand Where is their potential fraud with their expenses, where their suppliers maybe sending them duplicate invoices by accident? But Ari, I picks that up. So we are taking the space to a completely new level, and it's it could be more exciting. Honestly, >> well, the amount. You know, we go 1,000,000 shows a year, maybe a little bit less, But we always hear data is oil data is gold. It is. If you have access to it, you can extract insights from it really quickly and be able to act on it faster than your competition. >> Absolutely. You have to be able to normalize the data first informal, so you need a I capabilities. To do that, you have to access a massive data store you have to anonymous. The data obviously needs to be very, very secure, and then you have to draw insights out of that data. And one of things I share this morning is that we've given our customers just in 2019 more than 18,000 prescriptions of things they should consider, for example, putting some suppliers on hold if we think there's some risk with those suppliers. So absolutely, it's a I, but it's a I as the underlying element that brings out what we call community intelligence. And that's what's what's so powerful >> and the community as well, another really kind of under town that I felt and heard this morning from us. It's a community of collaboration, thes air, other businesses benefiting from what others have learned suppliers as well. So the customer centric city, the supplier central city, is there. >> Absolutely. It's all about this community concept, and we have well over 1000 companies that we've helped spend smarter, effectively and their community because these customers air sharing both in person and online, best practices, ideas for doing things differently, ideas for stretching this space beyond where it's ever been before, and that's really rewarding and every individual customers getting the benefit from that. Eso This community is developing very, very nicely, and it's serving the purposes of establishing this category, this new category of businessmen management, that world driving toward >> talk about that because that's something that's pretty innovative for Cooper. Business SPEND MANAGEMENT The role of procurement has changed. The role of finance has changed. They have the opportunity to become very strategic and really drive top line value. Talk to us about business, spend management What it means, how Coop is defining it >> absolutely well. First of all, any person I am in the world, and I've been asked this question for well over a decade. Now, do you think your company is doing a great job in managing its spending on older business needs that the company has, and you never get a resounding positive answer that, yes, we're doing a great job. And if you ask them, are you applying information technology to that problem in an effective way? The the answers or even worse? So we are attacking this full on with our customers in establishing the space, and that means everything from procurement expense reporting to invoice processing, two payments strategic sourcing, spend analytics supplier management contract lifecycle management. All of these application areas working together in concert help companies get their arms around spending and manage it in a much more smart way. And that's what this is. This is all about. >> One of the biggest challenges is you think about poor I t. Because every every line of business, whether your marketing, finance or engineering anything. Oh, engineering. I want to use lock. Start using flack. Marketing wants to use salesforce market Whatever these tools are in, suddenly this proliferation of shadowing T that's right and challenging to manage. But you can imagine how many supplier contracts are being duplicated triplicate, ID and even within the same organization, not getting the ideal price. So one of the great things big announcement today is the expansion of the relationship with Amazon in the AWS marketplace and wow, c I ose I t folks are gonna be able to do >> a lot >> through the Cupid platform. Tell us >> girls, that's right. Well, first of all, it's powered by an open by technology that we've developed, which allows you to have a very seamless experience. It's a purchasing experience that feels just like you're out on the Web, looking for any kind of item that you'd like to buy. But now you'll be able to subscribe to Service Is Cloud based. Service is through the Amazon AWS marketplace, and these Air service is that obviously would be approved by your CEO be approved by the folks involved in checking that it's secure, approved by legal and also approved by procurement So you can procure these cloud based service is very, very seamlessly right out of Cooper into AWS marketplace and back. And we think it's going to allow for obviously more volume of controlled spend, but also visibility into that spends. So it's properly matters >> that visibility is. You know, it's a word that we use in so many different applications. We don't want better visibility in our lives. In general, that is not easy to achieve. You talked about kind of these four core categories. You actually mentioned Maur that Cooper delivers its procurement, its invoices, expenses that can imagine travel management contingent workers getting an organization, whether it's a big organization like a staples or a smaller organization, that visibility is massively game changing. >> Yes, I think so. And I think one of the things that allows us to view that is we've really empowered the central hub organizations. Many the ones you described to roll out platforms to the end users all over the country, all over the world, wherever these people have employees to take control over spend. But have that Spence still routed to preferred, contractually righteous kind of spend categories that give them the results that they want. So this is a platform that is getting wide, wide adoption. And I'll tell you one of our application areas. We've seen more than a three x acceleration in the number of users over the last one year simply because of the adoption is so broadly accepted. And that has to do with our design and technology. Make it very, very usable. Our design concept of the best, you wise. No, you are right. So that's really how we're getting to where we're getting with a customer committee >> Adoptions challenging, you know. And there's if you look at the number of applications that an organization has a gonna work our list of sites, there's a lot and they're only effective if they're being utilized effectively by all of the folks that need to be doing that talk a little bit more. I love how you in your general session this morning shared with the audience. What c o u P a. Each acronym means. But and I saw that on the website best. Do I know you? I know what are some of the things that you think Cooper is doing really well that are really facilitating that adoption. That's again, that's hard to achieve. >> Well, it's in each of the letters in Cooper. So first, a comprehensive approach. That's what the C stands for. So cover every area of spend in one platform. We've never seen that before in the history of enterprise software, about a lot of siloed solutions all over the place, people trying to integrate them. We've put this all on one comprehensive platform. Secondly, doing it openly. That's what the old stands for. So being able to integrate to any ear piece system integrates a whole host of systems you mentioned slack earlier. We integrate into slack you could approve or reject spent purchased directly and slack. You have to get out to Cooper to do it, but you're doing it. The date is captured in Cooper. You is the user centrist city, so putting all the weight on the application itself and less of the weight on the employees themselves. Right now, we support guided buying with support all these capabilities, but our focus is on. You don't need any guidance in the future. Should require in the gun she should be. It should be so intuitive. The P stands for prescriptive, and this is using this community. Data we were discussing earlier to give real prescriptive advice. Teach customer, but how they should be spending or best practices, expenditures or benchmarks of how they could approve in the A stands for accelerated. It's the time of deployment. We're getting our customers live in a matter of months. They're accelerating their business process internally. I shared a stat that our customers in the last 12 months have improved the speed of their approvals by 30%. That's an aggregate. That's millions of millions, hundreds of billions of dollars in spend buying. So these five there is really differentiate us and they're really the vision areas that we focus on is a company with our with our community of customers. >> I was looking at some of the numbers from Cooper. You guys have consistently managed to grow revenues over 40% your rear in your fiscal year. 20 Q one earnings, which was just what last month or so. So revenue up 44% year over. You're crushing Wall Street's estimates by more than a 10 point gap. Lot of moment in, As you mentioned, let's talk about customers because at the end of the day, that's what you're all working towards. I know some of your proudest moments are when you get to talk with customers whose businesses have been transformed and you're giving them that the ah ha moments all the time. I love this morning how there >> was a lot >> of the voice of the customer covered there from so many different industries. The impact that you guys are making it Rolls Royce, for example, and MasterCard massive. Tell me some of your favorite stories that really articulate the breadth and depth of the value that delivers. I >> love it when the story begins in a situation where the CEO or CFO of the company don't necessarily get it, but somebody within our community steps up and shows them the business case of what we could achieve together. And then we, as a team is a collective unit delivered on achieving. Looking at was on themselves. I mean, they're processing more than $2,000,000,000 a month >> through our platform. I >> mentioned Procter Gamble. It process more than $50,000,000,000. Star Platform. Now >> these air, >> not initials. These were early adopter customers. They didn't have to go in our direction. There was some individual in that company that saw the spark of opportunity seized it, got it approved and worked with us hand in hand to drive it. And that's the stories that I love the most. And I shared so many of them this morning, but there are literally hundreds of them. All over the world in this community were cultivated. >> There are, and it's that's I think there's no bread or brand value that you can get Van it being articulated from the voice of a successful customer who it's not just normal, agile. We're saving money. It's no, we're driving shareholder value. There are significant business imperatives that are being driven because procurement is changing. We got to react to pricing pressures and forces like consumer ization. You know, we think of way have these expectations as consumers private lives, of getting anything that we want within a day when it shows up, you forgot what you ordered. It was that fast. That's right, what you guys are doing to enable the business buyers to have that same capability in their business lives. But to get that visibility, that 360 is really interesting. >> And the key also is to handle all the complexity on the back end for them. I could tell you so many companies I know that a really proud of crossing their paper based invoices very, very quickly, but they may not even know whether or not they got the goods of service is for which they're paying the invoice. So we do all of that heavy lifting on the back end on the platform itself, alleviating then users from that complexity and allowing them to have the experience that's similar to the one that that you just described >> can imagine how much money is being wasted on paper. They probably have absolutely no idea, absolutely no idea where you guys launched an Index. The Cooper Business Spend Index Just, I think, a month or two ago this is behavioral based data that you're bleeding from your community. Talk to us about the coupe of business spent index and some of the insights that you're already uncovering about the economy. >> Absolutely so. One of the things about this business spending nexus. It's something I've been thinking about frankly for over a decade. Can we collect enough data that's statistically significant enough actually be a leading indicator to future economic sentiment. You think about the data. We're looking at an aggregate. We know the average spend companies have per employee. We know how long approval cycles are, and we know the changes in those approval cycles. We know what percentage of spend is actually being rejected. Verse accepted at a moments notice aggregated those air in combination are leading in the Kidder's to the sentiment that companies have about the future of the economy. So we backwards tested this index that takes an account, these three elements that just described back to 2016 and it's proven to show pretty strong correlation with the way the economy actually played out for many of those quarters that many of those quarters. So last quarter we released our first verse, our first data set of the business spending. Next. And it showed that future economic economic sentiment for the next 3 to 4 months is actually very positive now, in some industries, more than others. But now, with three months later and clearly, the last three months have been pretty strong. So we're gonna be soon releasing our next quarterly Businessmen index. And we're gonna be doing this every quarter. Try to provide the business community with insights about where things are going. That's what everyone of business wants to know, where things are going, not where things have been. And we think we're in a unique position to share that and also, you know, sort of unfairly build awareness for brand out there so that people understand >> what we're all about. >> But that's that's critical. I'm gonna be talking to China tomorrow. You think of awareness Acquisition? Yes, Yes. Advocacy. Yes. Check, Check. Check. Old three. Those are critical last question robbery. As we look at the impact that procurement and getting this visibility of all of the distances spend can have on the business. Where is it as it relates to enabling businesses to digitally transformed >> to be competitive? Well, look, underlying all of this is the digital transformation that's happening for every company in every industry, without a doubt. But the use cases we support us so quantifiable. That's so clear not only in terms of cost savings that only in terms of compliance only in terms of visibility and getting your arms around spent actually drive revenue as well. If you do spend management effectively, you can change the way consumers experience your brand. And I shared a number of those stories. MGM resorts to Lulu Lemon to the Leukemia and Lymphoma Society and others. If you can get your arms around the spent and get people in the company, the goods and service is they need in record time. They're better position to express the company's vision to help them push towards an incredible iconic customer experiences. And we're just so proud to be ableto power that for this fast growing community of customers around the world, >> such an exciting time. Rob, thank you for having to queue, but inspired 19. It's been great. It's for looking forward to talking with lots more of your of your folks as well as amazing innovators and thinkers like Susie Orman and Deepak Chopra. Wow. Awesome stuff. Thank you. Well, thanks for having us. Thank you. All right. For Rob Bernstein. I'm Lisa Martin. You're watching the Cube from Cooper Inspired 19. Thanks for watching.

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. Brought to you by Cooper. >> Hey, welcome to the Cube. Lisa Martin on the ground in Las Vegas at Cooper Inspired 19. Excited to welcome to the program. And gentlemen from Staples, a place I go to all the time we have Christy Oreo, VP of strategic sourcing. Hey, Chris, welcome to the Cube. >> Thank you. Glad to be here, >> So I was just a staples the other day getting office supplies. It's a go to Penn's files Folders, Inc et cetera. You name it. That is a place I think everybody on the planet knows. But I >> want to >> talk to you about the Staples business and how you guys now have control over 8000 suppliers. You've got this visibility in control, which I think every human wants and every element of life you know of 100% of your indirect spend under management. So given those big business outcomes, let's dissect that. Obviously, you're a cool customer. That's why you're here. Talk to us about a little bit about Staples. All the different suppliers you guys have, and some of the challenges that you came to Cooper to help erase >> Well, we had a lot of issues with Roque spend. Everybody was doing what they wanted in every location. We had no verification. We weren't consolidating our spend to get the best deals and get the best outcomes, lack of consistency, all the stuff you hear about. And since we've ruled out Cooper, we've got a lot of structure in place now, and we've got much better uniformity, much better consistency. We've dramatically lowered our costs through the use of the tool and some of the some of the rules that we've put in place as a result of of launching Cooper a couple years ago now. So we're really pleased with how it's helped us organize our business and really bring visibility to where we're spending money and showing us the opportunities and where we could go after her and save even more money. >> You know, you talk about rogue spending. >> One of >> the interesting disrupters of procurement and finance is consumer ization we all have. Whether we're going on staples dot com or something else, we're on Amazon. I need to buy this. We have this expectation as consumers in our private lives that we can get anything we want. We have to check with anybody. I one click. So then when we go in as business buyers, we sort of have the same mentality. But obviously the challenge there is, a lot of organizations don't have visibility into. Where has every single dollar going? How many different suppliers are we working with? Do we have duplicates triple kits everywhere to talk to me >> a little >> bit about the with a kind of cultural strategic shift that you guys are making now that you have this visibility? Well, >> everybody's happy with the results. That's >> always good right >> when he had his. When you have some success and you start to tell the story, then all of a sudden people's eyes get opened, and what's interesting is I don't think anyone does anything with malice. But if you have a general manager of a warehouse who believes that ex widget is what he needs to really Pel perform and do better, he's doing that with the right intentions. What he doesn't understand is everything else that's going on behind the scenes, and we have deals in place with suppliers and there's a level of consistency that we expect that our suppliers expecting that our customers expect and we can't have that experience be different. So once we can't explain that story and the tool helps us see where that spend is coming from, we go back. We have a conversation, and all of a sudden it's enlightening like, Oh, I didn't know. Now that I know Okay, I get it. Let me do what you want me to do or what you need me to do. So that's been the biggest shift I think is just sharing information and putting a spotlight on things when they come up and it happens even still. You know, we've rolled out now a little over two and 1/2 years ago, and we still have these things come up because you get new people and people change roles and, you know, as a business person there's folks I've done business with in the past that have earned my trust, and I want to do business with them again because I know what. When people get new roles, they do the same thing, and sometimes that's not what we need them to do. So once you explain the story and you tell them about it and you show him the results, they come onboard. It's phenomenal. >> Everything goes back to the user experience with customer, whether your customer is an individual buyer or a business of 20 people to a Fortune 500. Everybody in an organization is ultimately, in some form or fashion touching the customer. The customer experience is critical to delight the customer to drive higher customer lifetime value from that customer. Um, so having the employees onboard understanding we still want you to be able to manage your Ware house even more efficiently. But we need you to understand how we're gonna give you the tools to do it better. Ultimately, the end of the day, it's goes back to that customer and making sure you can keep extracting value from them. >> One of our core values is put the customer first, always, and that's at the heart of everything we do. It's not about buying things cheap. It's about buying things at the right value and giving the customer the best possible experience they can, so there may be less expensive ways to do it, but it may not deliver the outcomes we want, so it's not always about buying cheap. It's about buying and getting the best value for us so that we can deliver the right experience to our customers. >> Was that a >> mentality that staples had prior to bringing on Cooper? Or now? Because suddenly you're starting to You have visibility into everything you're going? Oh, cheaper isn't necessarily better in some of these areas. I think it's >> a It's a corporate philosophy that we've had. I think we we realize that people can shop anywhere for anything they wanted. Anytime. Cooper has helped highlight some some discrepancies that we've been able to kind of take out. I would say that Cooper's help with that, but it's also been just a core philosophy of the company for a long time. Cooper's helping us execute against >> that now, but you're right. Consumers can buy >> whatever it >> is. If it's a product like something you want to buy on Amazon or service. Maybe it's your Internet service provider. We have so much choice. Think vendors of any product testers that recognize that and sounds like Staples does. From a core cultural perspective. You're already in a better position to understand. I really need to find Tune everything under the hood here because they could go somewhere else like that. They can't. It's good to >> understand that. But Cooper gives us the data and the facts and the analytics to help prove out where we can make a change and where we can help the company and help our customers. So it's a combination of both. >> Let's Dig into that data was in one of the things that Robert seemed shared this morning was about. Since Cooper's been public, which was 2016 they have a five x increase in the amount of spend that is being managed in the Cooper platform. I think the number was is now 1.2 trillion dollars, a tremendous amount of data in this group of community that everybody can leverage and share. We often hear data is gold. It's the new oil it is and you're smiling if you can actually see it, right extracted value, Yes, talk to us about the amount of value that Staples is getting by this group of community with a ton of valuable data. >> I would say we're at the infancy of going into the Cooper community in terms of sharing information and gaining information. I'm excited about the little bit that I've seen, and I'm one of things I want to learn. Here is more about how it will work and how it can help us. What Rob shared this morning was very interesting to me, and I'm very excited to learn more about >> it. Sounds and you're right And even Cooper says, they're at the infancy of it. I think they have. A couple of 100 customers are starting to use the community to share intelligence. Eso It is early days, but it's also something that I think of when I go to events and we talk about, you know, devil's Community. It's a very collaborative that not only is it customer centric, also, supplier centric Staples is a supplier of a lot of other businesses. So imagine there's kind of double and did benefit. It's that could be gleaned by you guys from them. We hope so. >> I think we're you know, we're probably a more unique customer than many that Cooper has and that we are. We are a customer. We use the tools, we love the tool, but we're also a cellar to you guys and two other Cooper uses in the community. So we see both sides of the equation with Cooper, and it is interesting. T gain those insights and see how we can help both sides of the company. Help group is customers and our customers more >> if you look at >> the platform for procurement invoices, expenses. Heymans, where did you start a few years ago with Cooper and where are you now? In terms of all the different elements that are running through it? >> We started with a simple PIO management secure to pay. Then we instituted a no P o no pay policy, and everyone started using the tools. It really helped us change things We don't use it for. Expenses wear starting like, as I said, to start to use some of the analytics. I'm very interested in learning more about Cooper pay or out here virtual card usage. That's very interesting to me, so I'm curious to learn about that on. We'll see where we go from there. >> Cooper Pay was, I think I know it's just a few months ago in London, and we are excited to hear some more news about that tomorrow, how they're expanding that. But there's this visibility and control idea is so critical because of any type of organization. Whether it's a retailer manufacturer, it's a hospital. There's so much shatter, weighty going. But I t is really big challenge of reining in the cats, if you will in all these cats. Because we all know now that Robert likes cats. But it's one of the things that they're announced with Amazon is wow. I t can have access to buy all of this software, control it, deploy it, manage it through the Amazon marketplace. And you suddenly think, Wow, how procurement and t are gonna be aligning, joining forces and really affecting top line of of any industry. >> Yeah, I think in Staples are our relationship between procurement and our i t S t s department has been strong from day one. They were the biggest advocates of us getting the tool to help them gain control and kind of eliminates a lot of the shadow I t organizations issue. Does you mentioned so in our environment, we are excited about that. We embrace that we're trying. Thio forced that out. So we've always had that sort of very strong partnership with our I T team, and that's really what's helped progress the tool through the company with great success with them in the beginning. And then you start to tell the story, and more and more people are interested in. Wait a minute. You can help them save how much into the budget and where we can reallocate that money and what can I do with it? So it's been really exciting and sort of fun to be part of the transformation. >> And you guys have, what north of 17,000 users on the platform, >> today's wave? A lot, A lot. >> That's pretty quick >> adoption in a few years, a lot of people to train, to educate and and to have it become part of their normal everyday activities. >> Well, we're going through a relaunch now, and the Cooper team has been phenomenal in terms of training and helping my team with all the work that goes on behind the scenes that nobody sees and helping us develop training for all of our associates as we relaunch it, because we're really gonna change the tool. We were a couple of revisions behind Ah, now we're getting caught up. So there's a lot of change coming in September to my company and to Cooper and thrilled with the help that the Cooper team has given us the launch. This >> last question for you. Chris Staples, a 34 year young business. I was just talking with a gentleman from procurement and Lulu Lemon and much younger business. And you >> kind of think, Well, a younger business Have more nimble mind sets. Give your advice your best lessons learned to your peers >> at older, more established organizations, going through a change of really looking at getting complete visibility and all your spent advice to them. >> It's a bit of a cliche, but don't do what you did yesterday. You know, you've got to be open to change. You've got to let the you know, I always say, the month the numbers tell the story, and where is where you're spending too much and how do you fix that? And just because you love a supplier today doesn't mean you can't love somebody else just as much tomorrow. If they can deliver a better value, and a lot of times you can find out that your current supplier can give you a better value than you. Then you had before if you just start poking around a little bit. So my advice would be not to stick with the status quo. Just cause it's easy. Challenge yourself. Challenger team. Challenge the people you work with. Change is good. >> Change is good. Chorus. What a pleasure to have you on the Cube. Big. Thanks. So much for joining me. >> Thank you. Very nice. I appreciate it. >> All right. For Christie. Oreo. I'm Lisa Martin. You're watching the Cube from Kucha. Inspire 19. Thanks for watching.