Illia Polosukhin, co-author of Attention Is All You Need and co-founder of NEAR Protocol, believes today's centralized AI ecosystem is broken. In this episode, he explains why User-Owned AI is the path forward ā making systems private, verifiable, and aligned with users rather than corporations. We explore confidential computing, interoperable AI agents, and what a more sustainable AI future might really look like.Subscribe to The Neuron newsletter: https://www.theneurondaily.com
Full Episode
So one of the architects of the transformer model now says the system is broken. Today on The Neuron, Ilya Polosukhin joins us to explain why centralized AI is unsustainable and how user-owned AI could rewrite the rules of trust, privacy, and power in this new era. Welcome, humans, to The Neuron, AI Explained. I'm Corey Knowles. You're joined, as always, by Grant Harvey.
And today we're joined by Ilya. How are you, Ilya?
I'm doing well. Yeah, it's exciting times.
It is. It is. It's great to have you. So, for those of you watching who maybe aren't familiar, Ilya, his work helped literally shape the modern AI revolution. He co-authored the landmark paper, Attention is All You Need, which introduced the transformer architecture, which was the foundation for models like GPT-4, Claude, Gemini, and so on and so forth.
So Ilya, when you published that in 2017, did you and the team anticipate that Transformers would become the foundation of everything today? And what do you think about where we are now? Like looking at it from the perspective of 2017 to today, do you think we're in the early innings or are we approaching some kind of inflection point? What's your take?
Yeah, that's a good question. I think, I think there was like, the answer is, you know, yes and no, as always.
I think it was clear that there's like massive step function that transformers are bringing, but same time, it didn't feel, I mean, it wasn't clear that this is like the step function that they're not going to be another, like, you know, few of those before we get to, I mean, let's just call it AGI level. Yeah. I left Google in 2017 right after this work.
To me, I actually thought this rate of improvement continues because 2016, 2015, it felt like we're on exponential growth of AI back then. Wow. And so like what we're feeling now, like I kind of thought this is going to be happening in 2017, 2018. So that's why I was like, hey, I want, you know, we effectively, we started Near actually as an AI company. It was Near AI, as in AI is near.
And we were trying to build what now is called vibe coding. So in 2017, we were effectively saying, hey, just describe what app you want to build and we'll generate it for you. And, you know, it didn't really work very well because we didn't have enough, you know, GPU compute power. But, you know, this is actually how we got to blockchain.
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