>> Announcer: Live from Los Angeles. It's theCUBE covering Open Source Summit North America 2017. Brought to you by, the Linux Foundation and Red Hat. >> Hello everyone, welcome back. Our live coverage, theCUBE's live coverage, of the Open Source Summit in North America, it's a part of the Linux Foundation. I'm John Furrier your host, with Stu Miniman our co-host. Our next guest is Tanmay Bakshi, who is an IBM honorary cloud advisor, algorithmist, former CUBE alumni. Great to see you. >> Thank you very much! Glad to be here! >> You get taller every year. It was what, three years ago, two years ago? >> I believe yeah, two years ago, Interconnect 2016. >> IBM show... doing a lot of great stuff. You're an IBM VIP, you're doing a lot of work with them. IBM Champion. >> Thank you >> Congratulations. >> Thank you. >> What's new? You're pushing any code today? >> Definitely! Now today, getting ready for my BoF that I've got tonight, it's been absolutely great. I've been working on a lot of new projects that I'm going to be talking about today and tomorrow at my keynote. Like I've been working on AskTanmay, or course you know, Interconnect 2016, very first time I presented AskTanmay. Since then, a lot has changed, I've incorporated real, deep learning algorithms, custom, with tensorflow. Into AskTanmay, AskTanmay now thinks about what it's actually looking at, using Watson as well, it's really interesting. And of course, new projects that I'm working on, including DeepSPADE, which actually, basically helps online communities, to detect, and of course report and flag spam, from different websites. For example, Stack Overflow, which I'm working on right now. >> So you're doing some deep learning stuff >> Tanmay: Yes >> with IBM Watson, the team, everything else. >> Tanmay: Exactly, yes. >> What's the coolest thing you've worked on, since we last talked? (laughing) >> Well it would have to be a tie between AskTanmay, DeepSPADE, and advancement to the Cognitive Story. As you know, from last time, I've been working on lots of interesting projects, like with AskTanmay, some great new updates that you'll hear about today. DeepSPADE itself though, I'd like to get a little bit more into that. There's actually, I mean of course, everyone listening right now has used Stack Overflow or Stack Exchange at one point in their lives. And so, they've probably noticed that, a little bit, here and there, you'd see a spam message on Stack Overflow, on a comment or post. And of course there are methods to try and prevent spam on Stack Overflow, but they aren't very effective. And that's why a group of programmers, known as Charcoal SE, actually went ahead and started creating, basically this sweep to try and prevent spam on Stack Exchange. And they call it, SmokeDetector. And it helps them to find and remove spam on Stack Exchange. >> This is so good until it goes out, and the battery needs to be replaced, and you got to get on a chair. But this whole SmokeDetector, this is a real way they help create a good, healthy community. >> Yes, exactly. So, they try and basically find spam, report to moderators, and if enough alarms are set off, they try and report it, or flag it automatically, via other people's accounts. And so basically, what I'm trying to do is, I mean, a few weeks ago, when I found out about what they're doing, I found out that they use regular expressions to try and find spam. And so they have, you know, years of people gathering experience, they're experts in this field. And they keep, you know, adding more regular expressions to try and find spam. And since I, you know, am really really passionate about deep learning, I thought why not try and help them out, trying to augment this sort of SmokeDetector, with deep learning. And so, they graciously donated their data set to me, which has a good amount of training, training rows for me to actually train a deep learning system to classify a post between spam or non-spam. And you'll be hearing a lot more about the model architecture, the CNN plus GRU model, that I've got running in Keras, tonight during my BoF. >> Now, machine learning, could be a real benefit to spam detection, cause the patterns. >> Tanmay: Exactly. >> Spammers tend to have their own patterns, >> Tanmay: Exactly. >> as do bots. >> Tanmay: Yes, exactly, exactly. And eventually, you realize that hey, maybe we're not using the same words in every post, but there's a specific pattern of words, or specific type of word, that always appears in a spam message. And machine learning would help us combat against that. And of course, in this case, maybe we don't actually have a word, or a specific website, or a specific phone number, that would trigger a regular expression alarm. But in the context that this website appears, machine learning can tell us that, "hey, yeah, this is probably a spam post." There are lots of really interesting places where machine learning can tie in with this, and help out with the accuracy. In fact, I've been able to reach around 98% accuracy, and around 15 thousand testing rows. So, I'm very glad with the results so far, and of course, I'm continuing to do all this brand retuning and everything... >> Alright, so how old are you this year? I can't keep the numbers straight. Are you 13, 14? >> Well originally, Interconnect 2016, I was 12, but now I'm 13 years old, and I'm going to be 14 in October, October 16th. >> Okay, so you're knocking on 14? >> Tanmay: Uh, not just yet there, I'll be 14... >> So, Tanmay, you're 14, you're time's done, at this point. But, one of your missions, to be serious, is helping to inspire the next generation. Especially here, at the Open Source Summit, give us a preview of what we're going to see in your keynote. >> Sure, definitely. And now, as you mentioned, in fact, I actually have a goal. Which is really to reach out to and help 100 thousand aspiring coders along their journey, of learning to code, and of course then applying that code in lots of different fields. In fact I'm actually, already around 4,500 people there. Which, I'm very very excited about. But today, during my BoF, as I mentioned, I'm going to be talking a lot about the in-depth of the DeepSpade and AskTanmay projects I've been working on. But tomorrow, during my keynote, you'll be hearing a lot about generally all the projects that I've been working on, and how they're impacting lots of different fields. Like, healthcare, utility, security via artificial intelligence and machine learning. >> So, when you first talked to us about AskTanmay, it's been what almost 18 months, I think there. What's changed, what's accelerating? I hear you throw out things like Tensorflow, not something we were talking about two years ago. >> Tanmay: Yeah. >> What have been some of the key learnings you've had, as you've really dug into this? >> Sure, in fact, this actually something that I'm going to be covering tonight. And that is, that AskTanmay, you could say, that it's DNA, well, from AskMSR, that was made in 2002. And I took that, revived it, and basically made it into AskTanmay. In its DNA, there were specific elements, like for example, it really relies on data redundancy. If there's no data redundancy, then AskTanmay doesn't do well. If you were to ask it where it was, where's the Open Source Summit North America going to be held, it wouldn't answer correctly, because it's not redundant enough on the internet. It's mentioned once or twice, but not more than that. And so, I learned that it's currently very, I guess you could say naive how it actually understands the data that it's collecting. However, over the past, I'd say around six or seven months, I've been able to implement a BiDAF or Bi-Directional Attention Flow, that was created by Allen AI. It's completely open-source, and it uses something that's called a SQuAD data set, or Stanford Question and Answer Data Set. In order to actually take paragraphs and questions, and try to return answers as snippets from the paragraphs. And so again, integrating AskTanmay, this allows me to really reduce the data redundancy requirement, able to merge very similar answers to have, you know better answers on the top of the list, and of course I'm able to have it more smart, it's not as naive. It actually understands the content that it's gathering from search engines. For example, Google and Bing, which I've also added search support for. So again, a lot has changed, using deep learning but still, sort of the key-points of AskTanmay requires very little computational power, very very cross-platform, runs on any operating system, including iOS, Android, etc. And of course, from there, open-source completely. >> So how has your life changed, since all the, you've been really in the spotlight, and well-deserved I think. It's been great to have you On theCUBE multiple times, thanks for coming on. >> Thank you No, definitely of course. >> Dave Vallante was just calling. He wants to ask you a few questions himself. Dave, if you're watching, we'll get you on, just call right now. What's going on, what are you going to do when... Are you like happy right now? Are you cool with everything? Or is there a point where you say, "Hey I want to play a little bit with different tools", you want more freedom? What's going on? >> Well, you see, right now I'm very very excited, I'm very happy with what I'm doing. Because of course I mean, my life generally has changed quite a bit since last Interconnect, you could say. From Interconnect 2016 to 17, to now. Of course, since then, I've been able to go into lots of different fields. Not only am I working with general deep learning at IBM Watson, now I'm working with lots of different tools. And I'm working especially, in terms of like, for example Linux. What I've been doing with open-source and everything. I've been able to create, for example, AskTanmay now integrated Keras and tensorflow. DeepSpade is actually built entirely off of tensorflow and Keras. And now I've also been able to venture into lots of different APIs as well. Not just with IBM Watson. Also things like, we've got the Dandelion API. Which AskTanmay also relies off of Dandelion, providing text similarity services for semantic and syntactic text similarity. Which, again, we'll be talking about tonight as well. So, yeah, lot's has changed, and of course, with all this sort of, new stuff that I'm able to show, or new media for which I'm able to share my knowledge, for example, all these, you know CUBE, interviews I've been doing, and of course all these keynotes, I'm able to really spread my message about AI, why I believe it's not only our future, but also our present. Like, for example, I also mentioned this last time. If you were to just open up your phone right now, you already see that you're, half of your phone is powered by AI. It's detecting that hey you're at your home right now, you just drove back from work, and it's this time on this day, so you probably want to open up this application. It predicts that, and provides you with that. Apart from that, things like Siri, Google Now, these are all powered by AI, they're already an integral part of our lives. And of course, what they're going to be doing in our lives to come is just absolutely great. With like, healthcare, providing artificial communication ability for people who can't communicate naturally. I think it's going to be really really interesting. >> Tanmay, it's always great have you on theCUBE. Congratulations. >> Tanmay: Thank you very much. >> AskTanmay, good projects. Let's stay in touch, as we start to produce more collaboration, we'd love to keep promoting your work. Great job. And you're an inspiration to many. >> Tanmay: Thank you very much, glad to be here. >> Thanks for coming on theCUBE. Live coverage from the Open Source Summit's theCUBE, in Los Angeles. I'm John Furrer, Stu Miniman. We'll be back with more live coverage after short this break. (upbeat music)

(upbeat music) >> Narrator: Live from Las Vegas, it's theCube covering InterConnect 2017. Brought to you by IBM. >> Okay welcome back everyone. We're here live in Las Vegas the Mandalay Bay for IBM InterConnect 2017. This is the Cube coverage I'm John Furrier my cohost Dave Vellante, our next guest is our famous Cube alumni, Tanmay Bakshi welcome back to the Cube. Now you're a cognitive developer and your new business card as part of the Darwin Ecosystem says Algorithmist. >> Dave: Algorithmist. >> Algorithmist, yes. >> John: Welcome back. >> Thank you, I'm very glad to be back on theCube. And yes, of course, as I said, I'm working on many new projects with artificial intelligence, and, of course, IBM Watson. Including ones that are provided by Darwin Ecosystem. And of course, we're working on this really interesting project called A Cognitive Story, which you will be seeing more about on my talks on Tuesday and Wednesday. The Cognitive Story is basically this collaboration between IBM, Darwin Ecosystem, Not Rocket Science, and me. Basically we're working towards really using the power of cognitive in order to change people's lives in a positive way. That's what I'm doing at the Darwin Ecosystem, generally, with IBM Watson and AI. >> Last year, we had a great chat. I remember talking about algorithms, the software, super fun. What's changed in the past year? Give us the update on you. And, two, what's changed in the code? >> Definitely. >> What are some of the things you're working on? >> Yeah, sure. So, since last year, first of all, a lot has changed. A lot of new trends have emerged in the general topic of technology, like Cybersecurity, something that people are starting to take a lot more seriously now. With things like AI and IBM Watson starting to be incorporated in with that. And, of course, though, really from my side, what I've mainly been doing is not, I've actually started to work not only with IBM Watson's cognitive capabilities, and not only the cognitive capabilities provided by these services, but also my own custom services. Crowd by neural networks, and other machine learning algorithms. Like, just for example, A Cognitive Story is powered by my own custom coded neural networks. And that's why, of course, I've been given the designation of Algorithmist. Because I love to work with algorithms, fine tune them, and, of course, design them. So that's actually what's been going on for the past year. But mainly, I guess you could say now my real focus is on how we can use artificial intelligence and cognitive computing in order to first of all, amplify and really augment human capability, and, of course, how we can use it to change people's lives in a positive way. Especially in fields like health care, where we can save people's lives with this technology, where we can make people's lives easier with this technology. Like, just for example, what IBM Watson is doing, for people with Autism, and how it's helping them with the applications that it provides. What IBM Watson's doing for the elderly in India, with the new Gentoo Robot that IBM Watson is creating, and so much that Watson is doing with healthcare. That's really what I'm focused in, with cognitive computing in general. >> What are some of the algorithms that you've been working on? What's the intent? >> Sure, well, I've actually been working on a lot of different algorithms. Mainly in the AI space, and, of course, how we can create neural networks to understand brainwave patterns. And you'll be seeing more of that on Tuesday and Wednesday, with The Cognitive Story. But, I've also been working, of course, on algorithms that I've already created, as I said, AskTanmay, you probably remember that from last year, the NLQA system. I've been working more on AskTanmay, and, in fact, in June, in Developer Connective last year, I actually open-sourced AskTanmay. So, of course, I've been working on that, improving it. I'm about to release Version 3, which is really fun. And, of course, since it's open source, I love to share my knowledge with this code so that other people can learn from it and learn how to use this type of AI technology in their own applications, as well. >> As a young, next generation, mogul, software mogul that you'll soon be, you're already one now, but you're still young, you've got a lot more ways to go, but you're living in a great time because, I wish I could be your age right now, because machine learning is really hot right now. And it's growing because of the cloud. The cloud gives you scale and compute power, and there's also a cultural vibe going on around social good. So, talk about machine learning, what you're excited about there, specifically, and some of the things that you see, from your generation of developers around this desire to provide social good. >> Yeah, definitely. Well, I guess we should start off with, really, my main focus of interest, in fact, as you said, are really cloud computing, cognitive computing, and IOT. Because in their respective fields, they are the next level of computing. And, in fact, we're already starting to adopt them. Cloud computing's already been adopted on a huge scale. Cognitive computing, we're getting there. And IOT's, again, starting to be accepted by a lot of different people. >> And you might not even get a driver's license because by the time you get your driver's license there's going to be autonomous vehicles. >> Exactly, and so, of course, IOT's being used everywhere, and so is cloud computing and cognitive. So, really, what I've been focused on in the past year is, first of all, trying to get developers really interested in cognitive. But as you said, developers are really interested in doing social good with these technologies, and, just imagine this, what we're doing with The Cognitive Story right now is, we're basically, for example, I can't, of course, go into too much detail about this right now, yet, but we are basically taking this cognitive services and we're allowing people who don't have the natural ability to be able to express themselves, or communicate, or move in any way, really, to be able to express themselves, and communicate their decisions, and communicate their emotion, or whether or not they're comfortable, and more, through this cognitive system. And, of course, that's why it's so interesting, because imagine if you can't talk, and imagine if you know that, OK, I want to do this, but you're unable to express that, you're unable to communicate that to the people around you, that means that you're quite literally trapped in your own body. And having cognitive computing able to come in and allow you to communicate, and create your own, I guess you could say, unique language using these brainwave patterns. That's something that I absolutely believe is, I guess you could say, the greatest gift, ever. To be able to give you the ability to communicate through artificial intelligence. That's really why I love working the healthcare field. >> Now, am I right, you've written a book? >> Yes, actually, and it actually started from last InterConnect. Last Interconnect, I started, and now I'm actually done writing my book, called, "Hello Swift!: IOS App Programming "for Kids and Other Beginners" and it's actually currently available for pre-order on the publisher's website, as well as lots of other book stores online. Of course, the final hard copy will be released soon. But basically, this book is really targeted towards getting the youth, and, really, kids, interested in programming, and specifically, IOS programming through Swift. And, of course, as you know, Swift is open-sourced, and I really support open source software. >> What are some of the cool things young kids want in software these days? Because, like I said, there is a tool chest of great stuff coming on, like composable software, Lego blocks, which people called like Lego blocks. What are some of the cool things that kids want these days? >> Well, there are a lot of things. But I'd actually like to highlight the main way that I like to get the youth interested in coding. And it's by showing them something that they find really interesting. For example, something that they see in movies a lot. Like, for example, artificial intelligence is the absolute perfect example of how you can have something, like artificial intelligence, that can get kids interested, and the youth interested, in these technologies like programming, in order to start to get them programming. Because of course, we need them to be prepared for their future. >> Gaming and AI are two, like, Sci-Fy is AI, kind of a cool, futuristic. And then gaming, also, is very interactive, immersion-based. >> Exactly, and, in fact, that's why a lot of companies are starting to merge AI and games. And, of course, virtual reality. Virtual reality is something else that, you know, kids, and really everybody, is really interested in nowadays. If we can, and in fact, we are, taking these AI technologies and incorporating them with these other technologies, like gaming, with the virtual reality, augmented reality, mixed reality, and we're trying to create this really interesting mix, especially for kids. And also, one more thing, here, is that not only are we doing this, AI is so diverse, it's all around us. It's on your phone, it's on your smart TV, it's in your car, and that's really why we should be showing the youth that this is all around us. We need to start adopting these technologies. >> Last year, I asked you the question, take us through a day in the life of Tanmay where you had a discovery. So let's play that back this year. Give us the time this year where you had a discovery. It could be super cool, or maybe just a breakthrough in some small way that was a notable that you'd like to share. >> Yes, and that actually happened recently. And again, I'm going to take this back to just a few weeks ago, actually. When I started working with, I mean, I had actually been working with my own custom machine learning algorithms for quite some time, since just after last InterConnect, actually, I started working with my own custom algorithms for machine learning. But a few weeks ago, I actually started working with those custom algorithms in the healthcare space. And one application that I've created that I find, actually, quite interesting because of the capability it has to help doctors, and I'll tell you this in a moment, is that it's an application that can take 69 attributes about any patient, OK, and it can actually tell you if they have a hearing disorder. And if so, what's their hearing disorder. The reason this is so great is because this can be a great help to audiologists, for example. And, in fact, I am actually in communication with an audiologist from the UK, and we're collaborating with him to try and see what this could hold in store for the future of audiology, and the future of healthcare, in general, with artificial intelligence. Apart from that, though, The Cognitive Story is another great project, where, of course, I'm trying to combine machine learning with these extremely powerful capabilities that Watson provides in order to create a great mix. In order to help people express themselves even though they don't have the natural ability to do so. >> So, Tanmay, obviously you are a big supporter of open source. You said earlier you open-sourced some of your algorithms, AskTanmay. What's been the response? Have you had contributors? >> Yes, actually, and that's the greatest part about open source, because, now, the thing is, let's just say there's some issues with AskTanmay, there's some, as you know, this is general open source stuff. But now, Ask Tanmay is really, I guess you could say, evolving much faster than I could ever have programmed it because there are many people coming to me, collaborating with me, helping out, submitting issues, pull requests, and more. And with AskTanmay, especially, now I'm about to release Version 3.0, as well, because I was able to get that help from the community. And, of course, because of that, not only does the community help me, but I am able to help the community by sharing my source code so they can learn from that and build their own QA systems on top of it. >> Awesome, so give us the report card on Bluemix and Watson. And be fair, now, I know you're IBM Champion. >> Yes, now, IBM Bluemix and Watson, I can tell, especially Watson, it has evolved a lot since last InterConnect. Of course, the new services that they're providing, like the Natural Language Understanding service, and more. And really, what I believe, is that not only are they providing these new services, but they're also improving their existing services. Like the Visual Recognition Service, how they're doing the image similarity, how they're improving their default classifier, how they are merging it with the Alchemy Vision services in order to make it even more powerful. And of course, the new, live training features that they're incorporating into visual recognition. How they're improving speech-to-text, and they're generally taking all of these Watson services that already exist and making them even more powerful so developers can really leverage them in their applications. Apart from that, though, IBM Bluemix has been going great, as well, with the new services it provides, especially from SoftLayer. Of course, Bluemix is going great, Watson has been rapidly evolving, as well. >> I notice you've got your IOT Watch on, the Apple iWatch. I bet you've been doing some stuff with IOT. What are some of the wearables you think that are needed right now? Because we had the founder of IndieGoGo on and we know the success of the crowdsourcing is there's a lot of tinkers and inventors out there who now can be up and running, so we're expecting to have a big maker culture growing exponentially around new stuff. So, what do you see that's needed from your generation? Chip implant in the brain? What's going on? >> Well, of course- >> What would you want? >> Well, in terms of, I guess you could say, wearables, there are a lot of different things that people are doing with wearables, including virtual realities. One of the main things that I believe is, I guess you could say, the most trending topic, in terms of wearables, of course watches, we've got glasses now that they're creating, like the Microsoft Hololens. And all of these different products that are focused around basically being able to, I guess you could say, run have these technologies available on your body. On yourself, quite literally. And to make it so easy to use. And really, what I believe is that one of the main things that's really going to power these wearables is AI, artificial intelligence. For example, even the Apple Watch has AI features in it. I mean, all virtual reality is powered by artificial intelligence, as well. And without that, it becomes extremely hard if not impossible for people to code in things like virtual reality. So what I believe is that we need, I guess you could say more adoption to these cognitive technologies. And we need people to adapt to it in their everyday environment, and really accept that it's all around them. And that's it's going to be extremely hard to live without it. Of course, we need to start getting the youth involved in these technologies, for them to be prepared for that future in which cognitive computing is everything, and, in fact, cognitive computing isn't just the future. It's the present, as well. That's why we need to start getting prepared for it. And that's why it's all around us. >> John was joking earlier about you getting your license. You're 14, now, is that right? >> 13, actually, about to be 14 in October. >> OK, right, so soon to be 14. So you'll probably get your license and still be able to drive. In two years we're not going to have totally autonomous vehicles, but- >> John: Maybe 25 years. >> What are your thoughts on that, though? What's the driving age in Canada, 16? >> Yes, I believe 16. >> Yeah, OK, so, you know, 16 years old, it's a symbol of freedom, you know, you get autonomy, and, you know. What's your feeling about maybe the next generation and them inheriting autonomous vehicles and not having, you know, the stick shift to drive, like when we were kids, and we all learned on the stick shift. What do you sense that? What do your colleagues and your other friends say about that? >> Sure, so, now, self-driving cars is something that is already being worked on, heavily, actually. It's a big research topic. Tesla, huge company that's really working towards self-driving cars, autonomous cars. They've already got, like, half of that done. They just have to work on the last half. Of course we've also got Google working on their self-driving cars, and so many other companies who at least aren't creating self-driving cars right now, or most are, actually, starting to work toward self-driving cars, including Uber. In fact, Uber is creating their own self-driving taxis that can take you around the city without you actually having to have a driver. But the thing is, what I believe, is that this AI technology is powerful enough to be able to work with these autonomous vehicles and more. It's just that there are a few, I guess you could say, rough edges that need to be worked out with these technologies, which I believe can be done. It's just a matter of time before we are able to get completely autonomous cars on the road. It's just that there might be a few issues with the ethics of self-driving cars, and that's an entire topic on its own. That would require an entirely separate interview. But, generally, I think autonomous cars, that's a great, great place to go with artificial intelligence, because that could completely eliminate, or at least significantly reduce, the amount of, for example, human error there is in driving. And, of course, get you around traffic faster. And, generally, maybe not even have traffic jams. There's just so many advantages to having autonomous cars. And, of course, that's why cognitive computing is all around us. >> So, AI is hot, IOT is hot. You're hot, you've got a great fan base. We know that from last year. The reaction from our audience was spectacular. >> Tanmay: Thank you. >> You almost won our Cube Madness competition because you retweeted all your followers, or all your YouTube followers. >> Tanmay: Thank you. >> Congratulations, great to see you. Come back on the Cube. >> Thank you, it's great to be on theCube. >> OK, we'll be back with more from theCube Live here in Las Vegas where IBM InterConnect, AI, cognitive computing, collective intelligence, all the data, here on theCube. We'll be right back with more after this short break. Stay with us.