Naveen Rao: 4D Computing, AI's Energy Wall & Beating Biology

SPEAKER_1 (0:00)

Naveen Rao, co-founder and CEO of Unconventional AI, which is an AI chip startup.

SPEAKER_2 (0:06)

Best known for building and selling two deep tech companies.

Naveen Rao (0:09)

Naveen is kind of definitionally outlier founder. When I came there, we had about a $20 million business, and it was, you know, 700 or 800 million when I left. I don't think you really understand something until you can build it. Just because something is tried does not mean it's wrong. I'm the opposite of an AI do-mer. I think AI is the next evolution of humanity. We need innovation on the hardware substrate to actually build true intelligence.

SPEAKER_1 (0:31)

Please welcome Naveen Rao.

Naveen Rao (0:45)

Great to be here.

You know, switching gears a little bit to AI now, which you may have heard a little bit about.

It's super exciting to be at this conference specifically because as was said in the intro, I'm the opposite of a Doomer. I think AI is one of those transformational technologies that humanity has ever created and will enable us to get to that next level of evolution, which I'm here for and this is sort of the anti-Doomer conference. So let's go.

So before we get going, I'll tell you a little bit about myself.

It's kind of weird. I'm really right where I wanted to be my whole life. This was me at about five or six years old, something like that. We had a computer very early on, so I'll date myself, but this was in 1978 We got a computer. This is probably in the early 80s. Learned to program when I was a little kid. I just thought it was like a puzzle.

I became an electrical engineer really because I enjoyed sci-fi and always wanted to think about how I could make an intelligent machine. And then after a career in building computers, I went back to school and got a PhD in neuroscience. The idea was like, let's go back to that thing. How do we make computers intelligent? And fortunately, the whole world kind of moved in this direction. So as a technologist, it's sort of the dream right now.

A little bit about me from a company entrepreneurship standpoint. I actually founded the first AI chip company called Nirvana Systems. So this was in 2014 If anyone remembers back then, there was no AI, or at least not in the common vernacular. And it was really hard to actually convince people this is important, much less to build hardware around it. Now you heard from Jensen up here, the largest company in the world, the hardware company, because of AI. So we were early on. I think I sold the company way too early to Intel. But I started and ran the AI group at Intel.

After I was done with that in 2020, I actually started thinking about the next problem, which was how do we build bigger models, like the large language models we talk about today? And it was about how do I build the infrastructure to build those models? So we started platformizing GPUs and enabling it to scale, and making that easy to use for other people. And after ChatGPT happened in 2022, we were kind of the best game in town for people to start building their own models. So took off really fast. We decided to actually join forces with Databricks. That was in 2023, and actually that's a quarter of the total revenue of Databricks today. So a lot of fun doing that whole thing with All-In team at Databricks. And now I want to tell you about Unconventional AI, which is rethinking the foundations of how a computer works. So we're going back to first principles here, to really try to build a new machine. Computers have worked a certain way for a long time. We want to rethink that for the singular purpose of making something very power efficient. And the goal has been within, it was initially within five years to get to a 1000x power efficiency. I've actually revised this to three and a half years because things have gone faster than we anticipated. We've actually solved very deep scientific problems quicker because of AI, interestingly enough. So, just a little bit how we organize, like we're truly a top to bottom company. We start with theorists. These are people with like math PhDs and theoretical neuroscience, that kind of thing. They come up with concepts that we think would effectively give us more power efficiency from the perspective of moving less information around. And we then translate that into models that do real things, train on real data and evaluate it against real criteria. So it's kind of the rubber hitting the road of these concepts. Then eventually we have to actually build something physical. So these are people who architect a physical circuit, actually design those circuits, model them and see if it actually works. So we try to connect this whole stack together.