#37 - Uma Roy

Balaji (0:00)

Uma, welcome to The Network State Podcast.

Uma Roy (0:02)

Thanks for having me.

Balaji (0:03)

Awesome. You want to introduce yourself briefly?

Uma Roy (0:04)

Yeah, so I'm co-founder and CEO of Succinct. Succinct is an applied cryptography company. We're probably best known for making the fastest zero-knowledge virtual machine, ZKVM for short, in the world, known as SP1. For those of you who aren't aware, ZK is this really powerful cryptography technique where it lets you prove to someone else something is true without revealing all the details. Kind of the canonical real-world example is that, if I can prove to you that I'm over 21, without revealing my birthday or my home address or anything like that. So instead of showing a driver's license at a bar, you can just show them a proof that you're of age.

We built this ZKVM, which, how can I describe it? I would say it's somewhat like a foundation model for cryptography. So if you want to prove really complex statements in ZK, such as a roll-up state transition function or very complex predicates, the thing we built makes it super easy. You just write normal code, you stick it in a DASP1, and out comes the proof.

And then we made it super fast and really easy to use, which was awesome. And I would say right now Succinct, although historically our ZKVM has been used mostly for proving blockchains and proving roll-up state transition functions and things like this and Ethereum and other chains, right now we're really excited about the potential of cryptography to solve a lot of the problems that AI poses. I think Balaji has been an extensive tweeter about this topic for many years. You're very ahead of your time, honestly.

Balaji (1:37)

Thank you.

Uma Roy (1:38)

And so yeah, I think honestly, that's probably one of the most important things cryptography can do right now. And there's finally a clear catalyst, every model release where the image stuff or video stuff gets better and better, it's like we need cryptography as a defense. So I think it's time for cryptography to be on a societal stage right now as a solution to all the AI stuff.

So I'm very excited about that.

Balaji (2:01)

Awesome. So yeah, actually, many years ago, partly actually because of AI, but also with social media when people are talking about misinformation, disinformation and so on and so forth. Years ago, I remember I tweeted something and I was like, oh, so you want to ban lies on the Internet? Okay, give me a function that says whether the Riemann hypothesis is true.

Right? And so that's a reduction at absurdum where we don't know whether it's true, and it could be true, and it's plausible that it's true, but there's many things in math which have really arcane counter examples that you get up to n equals whatever and it's actually not true.

And so, but as I thought about that, I was like, well, how would you code trugle, t-r-u-g-e-l-e, you know, if you were actually going to do it, right? How would you do it? And the thing is, LLMs get you some of the way towards that, right? Because they will take a statement and they'll do at least a probabilistic search at the literature and pull things up and so on and so forth, right? And the thing is, though, of course, those assertions themselves need to be underpinned, the citations, and then that's how you get to on-chain everything. And so my view is like with LLMs, actually you can kind of show a version of this today. If you ask any LLM to summarize some major crypto hack, it will show you probably some link that shows some on-chain block explorer record among other things. And so that's currently only used to document financial things, like the on-chain transaction during, let's say, FTX had a hack or whatever during that period, right? But as more and more things get logged on-chain, then more and more references from LLMs will point to on-chain events, and we get what I call the ledger of record, and I think Succinct could be maybe a big part of that. So you had some slides, so maybe you want to go through your slides? What's your background by the year? Born in the US, what's your spiel?

Uma Roy (4:15)

I was born in the US. I went to school at MIT, was a double major in math and CS. I've always really loved math, so that's how I got into ZK.

And ZK and cryptography have a lot of fascinating math, and that was really the draw for me. And actually, before ZK, I was doing some AI stuff, so I was at Google Brain doing research into early LLM, so this was pre-GPT. I was doing some stuff with BERT back then. So I'm familiar with that world, and now it's exciting to see the synthesis.