Konstantin Kisin

And so to your point, the people in Silicon Valley, they're getting tremendous productivity out of these.

These are people who are getting paid, you know, who are becoming 3x, 4x, 5x more productive as a result of using these models.

So far, because these models have been really good at text-in, text-out work, that is software engineering.

Software engineering is just a file of text, really, and you can just read every single text file, you can add more to it.

AI has been amazing at that.

It's been bad so far at, well, it's terrible at physical work, right?

So if you're doing any kind of blue collar work, robots are just not there yet.

But then even if you circumscribe it, even if you go in and look at, we're not just gonna look at software engineering, we're gonna look at all kinds of knowledge work, right?

All kinds of work that you can do on a computer.

Maybe 40% of the labor force is doing work that you can just do remote work.

If COVID happens again, you can put them on Zoom and they can do their work.

And AI companies now want to be able to do all of that work.

That requires training AIs to just be able to do anything that you can do on a computer an AI should be able to do.

And companies are saying, oh, we think we can get there in a year, maybe two years.

But that, I think, is explaining this discrepancy in what people are seeing.

Yeah, so I'll maybe tell you a story about my own use of AI.

Among the Silicon Valley people, I've been a sort of skeptic.

I've been the person who said, you think the singularity is going to happen yesterday?

I think it'll take five years, 10 years.

By this, I mean this idea that you'll have incredibly powerful AI systems that are able to do basically anything any human being can do.