Konstantin Kisin

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.

And some people in Silicon Valley are just, we'll get it later this year.

We'll get it in two years.

And I say, no, it'll take longer.

And even for me, I've had to admit that the progress has been pretty fast.

And here's a story.

So last year, like you guys do, I researched for my podcast.

Obviously, I read things, but then I also talked to these LLMs, the equivalents of ChatGPT, to research for a podcast.

And say last year I spent on the order of $100 on... If you add up my subscription to ChaiGBT and Quad and whatever and Gemini, there was a week where I was prepping for two different guests where in that prep, I just threw in a bunch of papers that are relevant to the research and a bunch of books and whatever into a folder.

And I just said to...

an LLM, hey, help me understand all this research so I can ask the person good questions about it.

And I turned on various things which make the model much more expensive.