Revisiting The Fundamentals of Crypto x AI with NEAR | 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
Welcome, everyone, to Delphi Digital's crypto AI conference. I'm John from Delphi Ventures. Today, I have 2 very special guests with me, Ilya and Alex, cofounders of NEAR. Most of you know NEAR as a blockchain project. However, NEAR's roots go deep into AI. Indeed, I know both of you guys started NEAR as a AI startup back in the day, which I'm gonna, which we're gonna talk about in this panel. But first, I wanna say I'm, like, extremely grateful to have both of you, working in this industry. I know you guys are, like, extremely experienced in kind of, you know, distributed systems, AI, softwar
you. Thank you for having us. Excited
to be here.
So I want to kick start things with, the Attention is All You Need paper. So for listeners, for context, for listeners who who may be unfamiliar, Ilya, previously worked in Google Research on natural language processing where she, coauthored Attention is All You Need paper. And this paper is basically laid the origins of transformers, basically the brains behind all the mainstream AI applications like Chatchipt that you, me, you know, millions of other users use today every day. So, yeah, Ilya, I want to ask you about, like to give us a simple explanation on, like, what's the big deal with the
For sure. Yeah. So I've been doing kind of machine learning, you know, what what we call AI now, for, for a long time before, even before joining Google Research. And kind of one of the fundamental challenges is how do we teach machines to be able to, you know, understand language, understand the context, and being able to answer questions. And so when I joined Google Research, I was really excited to work on that problem, kind of natural language understanding, but specifically the same way we test that people understand something they've learned, you know, in school, universities, you know,
Did did did the other Ilya reach out to you after kind of he realized this is kind of a breakthrough? Not
to me. No. But I mean Lucas, another co author is actually working OpenAI so I'm sure they're Yeah.
Did you did you know back then, like, how much of a breakthrough that was, like or or basically, like, like, the impact that it created in the world, I'm just assuming it must have surprised you. Or or did you know back then, like, that this was going to be become that big?
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