Talking to companies at ICML19
machine learning conference ai artificial intelligence industry academia deep learning hardware lidar graphcore
A short rant on sponsor companies at ICML and how to talk to them.
 All right, I quickly want to talk about kind of interaction with corporation company reps at these conferences, because to me it's still a bit of a secret or a bit of a not really clear of what to do. There's very different kinds of companies at these conferences, so some companies I feel are there to basically show off their technology, kind of wanting to use it. One example is for example Graphcore, the kind of new kid on the block for AI hardware in that they claim they have a chip specifically designed for the types of operations that machine learning applications do. So even more specialized than a GPU, and also they claim they are faster for equivalent kind of money spending than an Nvidia GPU, like a classic GPU. So basically you get much more bang for the buck. For now they just offer a cloud solution, I believe, and they're going to sell their cards through Dell. The way it works is they have kind of a low level compiler that will compile your model to these cards, and for now you can interact with it through C++, and then TensorFlow will come later, something like this. The thing about their card is that they have an extremely large memory right next to the compute unit, this would be kind of your traditional level one cache. That means that you get much faster access technically to your local variables, but then they don't have any kind of RAM, which means their entire card only has somewhat like 300 megabytes of memory, but they claim they can just basically distribute, if you have a large model you can distribute that over many cards, and then you'll get basically the speed up of the cards without having to sacrifice a model size. Another company that shows off really cool technology is a company that does LIDAR, and I forget the name right now, but when I try to look it up, they do a LIDAR sensor basically that is super tiny, and it costs a fraction of like a traditional LIDAR sensor. So I think they said theirs cost about $12,000, and it's really tiny, and has a couple of advantages compared to traditional sensors. As far as I understand, their lasers are mounted on the same chip, so they always point in the same direction, which reduces a lot of inaccuracies. I guess people would be interested in that, for self-driving cars and so on. These are kind of the hardware demonstrations that I've seen. Then there's other things, like there is a wellness center where you can get a massage, which is sponsored by the big companies, which is pretty nice, but I'm probably too much. I don't like these kinds of things too much. Maybe I'm just socially too awkward. For some companies, I feel that they're just there to recruit, and they don't really want to talk about what they do too much. So an indication of this would be a company where basically all of the reps at the booth are recruiters, so non-technical recruiters, that basically just kind of tell you what you can do as a career and not really what the company does as a whole. I never really know what to talk about then, because I feel like most people are interested and drawn towards interesting work, and if that comes with good working conditions, then that's a plus, but I don't feel for many people that that is the most important thing. So I could be wrong, and probably it's good that for some people it is, because otherwise everyone would take my jobs, the ones that I like. These companies will usually, if there is an engineer, they will not talk about too much what they do, like, oh, it's company secret and so on. So the funniest one was actually the NSA. Talking to the NSA was kind of painful because you kind of ask them, so what do you do? And they're like, yeah, machine learning. Because what I want to know as a researcher is, is there anything I could do there that I couldn't do anywhere else? So is there any unique problems that the NSA faces that actually demand new research, like demand new machine learning methods or some kind of change? So I ask this, and they're like, yes, there are problems like this. And you ask, like, which problems? And they're like, yeah, there are problems. We can't tell you. So everything's basically whatever. So I made it a game to ask them more specific questions and watch them, like, oh, this is classified. So yeah, if you're here, definitely check them out. It's fun. It's just fun to talk to them. Yeah, I feel to most companies, they're really interesting. I don't know more than half of them. So just going up, ask them what they do, kind of just get an overview over the landscape of what's needed currently in machine learning research. I think that's really useful, because as an academic, I tend to be very disconnected from the industry side of things and from what people actually need or want in practice. So talking to all these companies is really helpful to get an overview over that. Yeah, so but if you know a better way, I know some people are much more successful than me talking to companies at conferences. I'm definitely not the best at this. And yeah, if you have a better strategy, let me know. So I'm pretty happy so far. All right. That was that. See ya.
 All right, I quickly want to talk about kind of interaction with corporation company reps
 at these conferences, because to me it's still a bit of a secret or a bit of a not really
 clear of what to do.
 There's very different kinds of companies at these conferences, so some companies I
 feel are there to basically show off their technology, kind of wanting to use it.
 One example is for example Graphcore, the kind of new kid on the block for AI hardware
 in that they claim they have a chip specifically designed for the types of operations that
 machine learning applications do.
 So even more specialized than a GPU, and also they claim they are faster for equivalent
 kind of money spending than an Nvidia GPU, like a classic GPU.
 So basically you get much more bang for the buck.
 For now they just offer a cloud solution, I believe, and they're going to sell their
 cards through Dell.
 The way it works is they have kind of a low level compiler that will compile your model
 to these cards, and for now you can interact with it through C++, and then TensorFlow will
 come later, something like this.
 The thing about their card is that they have an extremely large memory right next to the
 compute unit, this would be kind of your traditional level one cache.
 That means that you get much faster access technically to your local variables, but then
 they don't have any kind of RAM, which means their entire card only has somewhat like 300
 megabytes of memory, but they claim they can just basically distribute, if you have a large
 model you can distribute that over many cards, and then you'll get basically the speed up
 of the cards without having to sacrifice a model size.
 Another company that shows off really cool technology is a company that does LIDAR, and
 I forget the name right now, but when I try to look it up, they do a LIDAR sensor basically
 that is super tiny, and it costs a fraction of like a traditional LIDAR sensor.
 So I think they said theirs cost about $12,000, and it's really tiny, and has a couple of
 advantages compared to traditional sensors.
 As far as I understand, their lasers are mounted on the same chip, so they always point in
 the same direction, which reduces a lot of inaccuracies.
 I guess people would be interested in that, for self-driving cars and so on.
 These are kind of the hardware demonstrations that I've seen.
 Then there's other things, like there is a wellness center where you can get a massage,
 which is sponsored by the big companies, which is pretty nice, but I'm probably too much.
 I don't like these kinds of things too much.
 Maybe I'm just socially too awkward.
 For some companies, I feel that they're just there to recruit, and they don't really want
 to talk about what they do too much.
 So an indication of this would be a company where basically all of the reps at the booth
 are recruiters, so non-technical recruiters, that basically just kind of tell you what
 you can do as a career and not really what the company does as a whole.
 I never really know what to talk about then, because I feel like most people are interested
 and drawn towards interesting work, and if that comes with good working conditions, then
 that's a plus, but I don't feel for many people that that is the most important thing.
 So I could be wrong, and probably it's good that for some people it is, because otherwise
 everyone would take my jobs, the ones that I like.
 These companies will usually, if there is an engineer, they will not talk about too
 much what they do, like, oh, it's company secret and so on.
 So the funniest one was actually the NSA.
 Talking to the NSA was kind of painful because you kind of ask them, so what do you do?
 And they're like, yeah, machine learning.
 Because what I want to know as a researcher is, is there anything I could do there that
 I couldn't do anywhere else?
 So is there any unique problems that the NSA faces that actually demand new research, like
 demand new machine learning methods or some kind of change?
 So I ask this, and they're like, yes, there are problems like this.
 And you ask, like, which problems?
 And they're like, yeah, there are problems.
 We can't tell you.
 So everything's basically whatever.
 So I made it a game to ask them more specific questions and watch them, like, oh, this is
 classified.
 So yeah, if you're here, definitely check them out.
 It's fun.
 It's just fun to talk to them.
 Yeah, I feel to most companies, they're really interesting.
 I don't know more than half of them.
 So just going up, ask them what they do, kind of just get an overview over the landscape
 of what's needed currently in machine learning research.
 I think that's really useful, because as an academic, I tend to be very disconnected from
 the industry side of things and from what people actually need or want in practice.
 So talking to all these companies is really helpful to get an overview over that.
 Yeah, so but if you know a better way, I know some people are much more successful than
 me talking to companies at conferences.
 I'm definitely not the best at this.
 And yeah, if you have a better strategy, let me know.
 So I'm pretty happy so far.
 All right.
 That was that.
 See ya.