Ilya Sutskever

Their words

So the reason there has been no diversity I believe is because of pre-training. All the pre-trained models are the same pretty much because the pre-train on the same data.

Their words

I think I think there'll definitely be there'll be diminishing returns because you want you want people who think differently rather than the same. I think that if they were literal copies of me, I'm not sure how much more incremental value you'd get.

Their words

I think what's going to happen is that the way competition like competition loves specialization and you see it in the market, you see it in evolution as well. So you're going to have lots of different niches and you're going to have lots of different companies who are occupying different niches

Their words

I maintain that in the end there will be a convergence of strategies. So I think there will be a convergence of strategies where at some point as AI becomes more powerful it's going to become more or less clearer to everyone what the strategy should be.

Their words

But I think the idea of very rapid economic growth for some time, I think it's very possible from broad deployment.

Their words

A human being, a human being lacks a huge amount of knowledge. Instead, we rely on continual learning. We rely on continual learning.

Their words

Number three, I think it would be really materially helpful if the power of the most powerful super intelligence was somehow capped because it would address a lot of these concerns.

Their words

I think in particular it will be there's a case to be made that it will be easier to build an AI that cares about sentient life than an AI that cares about human life alone because the AI itself will be sentient.

Their words

I do think that at some point the AI will start to feel powerful actually and I think when that happens we will see a big change in the way all AI companies approach safety.

Their words

Indeed, the whole problem, what is the problem of AI and AGI? The whole problem is the power. The whole problem is the power. When the power is really big, what's going to happen?

Their words

one of the one of the ways in which my thinking has been changing is that I now place more importance on AI being deployed incrementally and in advance.

Their words

Like basically I think I think that there is a big benefit from AI being in the public and that would be a reason for us to not be quite straight shot.

Their words

So there definitely for for research you need like definitely some amount of compute but it's far from obvious that you need the absolutely largest amount of compute ever for research.

Their words

And so because scaling sucked out all the air in the room, everyone started to do the same thing. We got to the point where uh we are in a world where there are more companies than ideas by quite a bit.

Their words

And it's just this, this is an example of how language affects thought. Scaling is what just one word, but it's such a powerful word because it informs people what to do.

Their words

Like it would be different for sure but like is the belief that if you just 100x the scale everything would be transformed. I don't think that's true. So it's back to the age of research again just with big computers.

Their words

At least for me, when I remember myself being 5 years old, my I was I was very excited about cars back then, and I'm pretty sure my car recognition was more than adequate for self-driving already.

Their words

What I meant to say is that language math and coding and especially math and coding suggests that whatever it is that makes people good at learning is probably not so much a complicated prior but something more some fundamental thing.

Their words

I think for example our intuitive feeling of hunger is not succeeding in guiding us correctly in this world with an abundance of food.

Their words

They have a general sense which is also by the way extremely robust in people like whatever it is the human value function whatever the human value function is with a few exceptions around addiction it's actually very very robust

Their words

I want to like emphasize that I think the value function is something like it's going to make RL more efficient and I think that makes a difference but I think that anything you can do with a value function you can do without just more slowly.

Their words

The thing which I think is the most fundamental is that these models somehow just generalize dramatically worse than people.

Their words

I don't think there is a human analog to pre-training.

Their words

The models are much more like the first student but even more because then we say okay so the model should be good at competitive programming so let's get every single competitive programming problem ever and then let's do some data augmentation so we have even more competitive programming problems

Their words

And one of the one thing you could do, and I think that's something that is done inadvertently, is that people take inspiration from the evals.