00:02:25 · Aditya Agarwal, Srinivas Narayanan
[00:02:25] S1: 100%. You know, we are all about the minus one to zero journey. I'd love to love to hear about your early years and your early influences in life. Right? We, of course, were talking just about it, that the love for science and math. And, course, if you're at SPC, you have to go to IIT Madras and you have to do computer science. So I think that was given and preordained. But talk to us about your pre influences early in life and what were the choices that you took to... Both on the early academic choices and career choices that got you here? [00:03:00] S0: Yeah. I grew up in Chennai. I think I've always been interested in math and science. So I was I was very interested in physics when I was studying for IIT. The contrarian choice would have been to study physics. Mhmm. I probably would have done it if IIT Madras had a physics program. I didn't wanna leave Madras. So I said... But... I said I'll study computer science. And I was always interested in computer science, but I would say physics was probably a bigger love at that age. But I enjoyed computer science tremendously as I was studying it as well. I was interested in AI as well coming to think of it because I took all the electives that existed back then. Believe it or not, I studied neural networks in nineteen ninety four, ninety five. It was interesting. It was exciting, but, you know, that was the AI winters. Right? So it wasn't really practical. [00:03:53] S1: We were almost having a renaissance moment around that time, right, at least in some academic circles around neural networks.
00:03:59 · Srinivas Narayanan
[00:03:59] S0: Nineties, yeah, it was sort of the winter. I think... Yeah. I did write a chess program back in 1994. It was not very good. And it's embarrassing to say being bad at chess coming from Chennai, by the way. So... But... Yeah. I mean, I was... I think I was always interested in AI, but it wasn't a real thing. I think I studied computer science. I studied databases in grad school. I worked in IBM research for a few years. The Internet bug hit, so I kind of felt like I should do something more exciting. So I've done two startups. The second one led me to Facebook. And even at Facebook, when I started, you know, the AI wasn't a real thing. So I worked on, you know, products having a lot of impact. But part of working on photos, you know, we were doing face recognition, and that was the seed of AI where I was exposed to it. And that... You know, this was back in 2012, and we were trying to figure out how to improve our face recognition systems. And we realized that there was something big happening in computer vision around that time when ImageNet happened. Yeah. So I got exposed to that. And, you know, and for a few years, I sort of still worked on other things. But then in 2016, I came back and said, okay. This is what I wanna work on full time. So I will always been interested, but I think there might be the moment. I was always also very practical that way. I always wanted to work on things that are impactful, not just interesting. And I think that combination probably in AI happened around that time. And so since 2016, I've been entirely focused on AI.
00:05:30 · Aditya Agarwal
[00:05:30] S1: It almost feels like at Meta, you worked through four companies. Right? Photos. You have Oculus. You have applied research, of course, the deep learning work around vision, right, around the same time that the AlexNet paper came out. So I'm just wondering, what is the process to gravitate to interesting problems? Or maybe how do you... Yeah. How do... What... What's your nose on these things?
00:05:56 · Srinivas Narayanan
[00:05:56] S0: Yeah. I mean, at Meta, we went through... You know, when we started, there was really... Mobile wasn't really there, so most of it was web. Four technological shifts or, you know, web, mobile slash cloud. ARVR honestly was a distraction for me. So I did that for a few years, but my heart wasn't really in it. So I actually came back to work on AI. And so AI was a very big technological shift as well. So I think for me, I've always been gravitated towards being at the bleeding edge and something extremely innovative, extremely exciting, but also extremely impactful. And I think maybe I've always been open to having a beginner's mindset. I'm willing to go back to the drawing room. It's not like, you know, I was born with AI. I didn't study AI for, like, twenty years. But just being to go back to the basics and, you know, bet on yourself being able to pick up and learn a new technology, I've been willing to do that, and I think that has served me pretty well. Then a lot of people are maybe maybe afraid of making a change. You know? You think of yourself as, you know, I'm a data scientist or I am a, you know, mobile engineer. And, I think you have to break these preset mindsets. And when something exciting is happening, just learn. Right? And so that has served me quite well.
00:07:07 · Aditya Agarwal
[00:07:07] S1: Well, that's interesting because one of the things that we internally at SPC also, when we're talking about, we're looking for people who have interesting taste in problems, right? And often these dots connect back. When you're looking back, they connect really well. When you're looking forward, right, and there are a bunch of things which might feel interesting, right, and which you might be curious on or about, right? What is the recommendation to people as they are thinking through this, right? Because personal curiosities often are different, right, and environmental changes are often very different. How should... What is your recommendation to people who are trying to look at what are the interesting problems or interesting areas? I
00:07:49 · Srinivas Narayanan
[00:07:49] S0: don't know if there is one process, but, you know, finding something that you will spend your time, entire energy thinking about, giving yourselves the space to explore because, you know, you're not gonna wake up one day and, like, some brilliant idea comes in. Oftentimes, you get passionate by actually doing things yourself. So I... That is one of the big reasons I love the SPC mandate about minus one to zero. You need the space to go and explore things. And if you don't do that, you're never gonna find that thing. Right? So give yourselves the space. Ideate. Be practical. Be hands on. But also find a problem that you have some deep personal connection to. Why is this important to you? Right? Like, do you spend... Do you see yourself working on this for the next ten years? What... Like, imagine what is the world that you want... Want to see different. Right? Yeah. And so when you find that purpose... And that can... A lot of time, it comes from some deep personal beliefs, some experience you've had in life, your interest. It's a combination of all of those things. Yeah. And, you know, find that purpose. I think one recent book that I read is is just a collection of quotes by Steve Jobs. I think it's called make something wonderful, if I'm not mistaken. It's just a collection of his quotes. Like, it's incredibly inspiring. You know, if you want inspiration for doing something useful, meaningful life, go read that. I think, you know, it sort of talks about one of the philosophies being, you know, don't take the world as granted. You being a passive observer, you know, you are an active participant. You have so much agency to change. You have, you know, you have your one life. You know, you shine briefly in the sky for a moment and die. I think that's the metaphor he uses. Yeah. Make full use of that. You know?