Using TensorFlow to enable research & production across many fields (TensorFlow Meets)

Key Takeaways

hi everybody and welcome to the 10th afloat developer summit I'm Laurence Moroney reporting from the tensorflow cafe and it's my pleasure to have Megan catch olya with me in this episode now Meghan great keynote you gave there was lots of great information on there and we had Jeff on the show a few minutes ago and he was talking about like some of the great stuff that's been done with tensorflow and we shared some great examples could you tell us about them yeah well actually there was one example I really liked in Anita's section as well also kind of right at the beginning there was the example about the planet discovery and the reason I really like this one is because it was someone in my team and it really was one of these things where someone came and it was there like I have this idea this data is publicly available can we try this I'm not sure if it's gonna work but I'm excited about it okay sure 20% project why not they're like oh how is it what's it like being in brain and on tend to flow I'm like oh one of my Swedes discovered planets it's it's pretty cool so what did you do so I think that's really amazing just because when you take a step back and think about it this is a person who has very strong software engineering skills he's good at machine learning he knows it but he's not an astrophysicist yep he's never discovered like doesn't stop with NASA or anything before it was just the data was there he was excited about trying it and we found a way to make a work I thought that was really to me that just a really cool example of like oh wow like there are these problems that before we're like well we can have a human sift through all this and maybe figure some things out right we can actually find things out better by using machine learning and then everyone's really excited about what we've found so I really like that one that one's one of my favorites it's not just discovering the planet but it's also a solar system that has multiple planets yes so being able to get to the resolution of saying hey it's not just we know there's a planet around this star many light-years away there are eight of them you know I think it's 30 light years anyway but I think that just blows my mind because it's not that long ago like he said it was only the top astrophysicists and astronomers we might be able to measure wobble in a star and say I think there's a planet there now what machine learned data we can have somebody go nope there's eight of them exactly you shared some examples in your keynote that I really like like protecting the rainforests and air traffic control right so what have you been involved in any of them or is your team not directly in any of those examples I don't think I do have a few folks who have worked on some of the medical examples that I need to talked about and then Jeff kind of talked more about as well I think those are really exciting and just because it's a way of augmenting doctors and helping them right you can give them more tools you can give them more information you can give them more data it's not that you can replace doctors but you can give them more help so that they can do their job better and actually help more people especially in places where they're just part enough doctors or aren't enough folks who have the right kind of training the right I think that's really exciting just to see the certain things like the the retina scans right the different all the other stuff they're doing in ophthalmology I've had a couple of folks who've worked on some of those projects as well but I always find those really exciting because it's applying machine learning to a problem we already know about but the results are so amazing just they you can make things better for people Jeff and I were joking it said but it's true it's like it's computer vision helping real vision yes I really like the air traffic control example because you know I used to live really right beside the main air traffic control center for New York and it was like the one thing that I learned is how stressful the job it is to and to think how quickly people burn out doing that job but then having something to at least the system obviously it can't replace them but to at least the system in that job because prediction and projection I mean it's that's what they have to do in split second that's correct the more data or the more information they can have at their hands or the faster they can get it at their fingertips the better off we'll be in making the right choices and helping direct everything correctly it takes a special gift to do that job so anything we can do to help them and keep us safer while we're in the air just just just really blew my mind so now of course all of this is made possible by tensorflow and you're part of the engineering team for tensorflow how does it feel to to be building all this or to be helping to build all this it's really exciting I mean think sometimes with it's like with any job you might get lost in the day-to-day of it right we have teams to run we have to make sure we're building the right things but I think the most exciting thing is when we get to take a step back and be like what's the community trying to do right what types of things are they trying to vote how do we help go in some of those different directions whether it's just make it easier for more people to use things because now the API is are simpler or those higher-level API is like Kerris or whether it's like okay we know there's really some experts out there who wants to just fine-tune and hand tune everything give them the capability to do that and tell them how to do it for a really powerful hardware so I think it's it's one of those groups especially at Google you don't see as many where they get to have this external community interaction I find that to be the most interesting thing because people externally are watching what we're doing we're held accountable to you know to the team or to the group we're held accountable to all the folks who are using tensorflow as well and who want to use it for different applications so I find that actually one of the most exciting things about tensorflow as a project is that it's not just about like oh we're doing something inside for Google no no we're really looking at like what does it mean for the community how are we helping all the different groups how are we enabling research how are we naming production so I find that the most the most part the people are awesome as well and I mean there are people out there with world-beating ideas and no way to implement them right and it's a part of what we're trying to do is to democratize AI so that they can go out there and they can implement them because we can't think of everything we're enabling and helping it's actually really cold as a board just outside the cafe where people have been writing their ideas like go check it out well I think we did this at the last dev summit as well and it's always really like overwhelming in a sense to look and see and like oh my gosh there's so many ideas there so many things people have already done as well it's so impressive some of them are super inspiring and some of them are hilarious my favorite is I saw some somebody wants to build a jazz musician they should they should talk to my Jess the next Miles Davis so thank you so much Megan it's been a real pleasure and thanks everybody for watching I'm Laurence Moroney and if you have any questions for me or if you have any questions for Megan please leave them in the comments below and we'll be sure to answer them and don't forget to hit that subscribe button thank you [Music] [Music]