Illia Polosukhin: Fixing the Broken System He Helped Create
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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. But I would just say, like, we expected Canada's growth to continue. And actually... It was more disappointing that it didn't. And it took some time until 22 for that to pick up. And now we're actually writing this exponential.
And I think now we're in inflection point from a resource and attention perspective because there's just so much... kind of focus on this now that I effectively never been. And I think because of this is just the rate of, rate of innovation is so much higher, right? Like the amount of, you know, money put in a compute, like all of those things are just like, you know, The numbers are crazy comparative to like five, seven years ago where, you know, you would train on like a single GPU and you feel super cool.
And now you've got billionaires buying chips out from under one another. Exactly.
And now you're like, hey, 100,000 GPU cluster. Like, what is this? Amateur hour? Yeah. Yeah, so I think generally we're in a section from kind of rate of research and innovation that's happening. Obviously, it's hard to predict different levels of kind of quality of models and also just adoption. Some of the adoption is being dragged by just, you know, there's a lot of industries who are still using pen and paper. Yes, AI is getting better at, you know, computer vision as well and you can you can potentially use it with that but uh obviously if your workflow is not even like digital you can't even like ai is not going to be that much help yeah totally um but i think like generally that that the we are kind of definitely on exponential and so um as i said we're living we're living in interesting times
We are. Yeah. I mean, that begs the question.
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