OLAS: How Multi-Agent Systems Will Shape AI's Future | Crypto x AI Event
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Before we get started, we'd like to thank our sponsors for making this event possible. Special thanks to our platinum sponsor, Olas. Olas enables everyone to own a share of AI, specifically autonomous agent economies. We're also excited to highlight our silver sponsors, NEA, empowering decentralized applications and blockchain ecosystems. Venice AI, a private and uncensored alternative to popular AI apps. MIRROR, unified AI infrastructure secured by crypto. And Therick, the first on chain multi agent system. To learn more about all of our sponsors, check the description below and dive in. Enjo
Hey, everyone. Welcome to the Delphi podcast. We're continuing with our crypto AI month series. And today, I'm joined by a very special guest, David Menorche, cofounder of Valerie AG, the entity behind OLAS and one of the leading protocols powering networks of autonomous agents on chain. David, very excited to, to have you join the podcast. How are you? I'm
good. Thanks for having me. Yeah. Yeah.
Is it, is it your first time, I assume? On
the Delphi podcast? Yeah.
Alright. Awesome. First timer. So I'm gonna I'm gonna dive right in and hit you with some some hard questions out of the gate, but I think there's been a lot of talk about the shape of intelligence, in terms of AI. And so I was curious to pick your brain. Do you think we are heading for a world of 1,000,000 models versus a handful of large hyperscale god models or a million fine tunes of those same five models. Those are kinda the 3 scenarios that I've seen, you know, people advocating for. Curious to get your thoughts.
Yeah. I mean, I can see arguments for all of them. Right? But I'm tempted to say the first category, so a 1,000,000 models. I I do think they'll have, like, a a shared route, to to some degree, But I don't think it will be maybe as prevalent as it is right now. Reason being that I think right now these models aren't really active, like learners' day. You know, snapshots of, like, certain points in time when the training data was assembled and these models were trained. Figure moving to more, like, you know, continuous, learners and, more agenda kind of, setups. And so I think that will cause t
Got it. Well, I think, us at Delphi are also betting on that vision quite heavily. So hope you are correct. So next, maybe we just touch on kind of, you know, your background a little bit, and why you and your team are the right people to, you know, kind of attack the problem that you're going after at Olas. Yeah.
So maybe I'll first start with the team and then, sort of, take it from there. So at Valry, we have 3 cofounders. There's my cofounder David, who is a CTO in at Bellry, and he has a background in cryptography, you know, published cryptographer, and a a lot of insights in sort of privacy tech, privacy preserving machine learning. These kind of topics are also something he has some experience in. My other cofounder, Oak, that's a pseudonym. He has a product a strong product background initially in sort of web 2, then came, into, the the crypto space, around 10 years ago, and, he's leading our al
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