People Have No Idea What Is About To Happen - Dwarkesh Patel

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TRIGGERnometry 1h 20m 4 speakers 8 chapters transcribed 3 months ago
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What is the significance of AI's rapid development?

Unknown 0:00
I've been the person who said, you think the singularity is going to happen yesterday?
Konstantin Kisin 0:20
I think it'll take five years, ten years. And even for me, I've had to admit that the progress has been pretty fast.
Francis Foster 0:28
Well, I guess the broader point is, is it going to, like, cure cancer at one point? Presumably it will.
Konstantin Kisin 0:33
I think at some point it will. I mean, just think of it as more people. If civilization had 10 billion more scientists, human scientists, would we make faster progress on aging? I'm sure we would. Here's another angle, mass surveillance. The AIs have the potential to make authoritarian societies much more sustainable and powerful than they have been in the past. A lot of the reasons that government has not been as authoritarian as it has in the past is that it's just physically not been possible. How do we make sure that humans don't get totally disenfranchised? Right. How do we make sure of that? I think it's a tough question.
Francis Foster 1:11
Dwarkesh Patel, welcome to Trigonometry. Thanks for having me. It's great to have you on. Actually, I was saying to you before we started, I'm a big fan of your podcast, and I listen particularly to the history episodes.

How might AI impact healthcare and disease treatment?

Francis Foster 1:21
But you've been described as Silicon Valley's favorite podcaster, and you write a lot about AI and tech. And that's actually the conversation we really want to have with you. Partly because a lot of people watching and listening to this, they've got lives, you know, family, work, et cetera. And they haven't been to California. They haven't been to San Francisco. They haven't seen a third of the cars on the road or 25% of the robots, basically. Like this is happening fast and a lot of people haven't caught up yet. And what we'd love to do is just kind of... connect people like you who really understand what's going on with a much more general audience. That includes us, frankly. So first of all, can you explain in broad brushstrokes what is happening with AI?
Francis Foster 2:07
I know it's a massive question, obviously, but do your best.
Konstantin Kisin 2:12
Well, I can explain it very concisely. The models are getting better. And then we can be a little less concise. I think it's, you're correct to point out that there's this huge discrepancy between what people are seeing in Silicon Valley and what people are observing outside. It's frankly because of how useful the models are becoming at certain kinds of things. So by models, I mean, you've seen Chad GBT. You might have heard of things like Gemini from Google. You might have heard of Clot from Anthropic. And you might be using these models to basically do the equivalent of Google search, using it to replace sometimes any Google search. Instead, I'm going to type it into chat GPT, see what chat says. What people are now using these models to do in a very powerful way is if you're a developer,
Konstantin Kisin 2:57
Some of the top developers in the world, some of the top researchers in the world, they're not writing code.

What are the potential risks of AI in authoritarian regimes?

Konstantin Kisin 3:04
They haven't touched a line of code since December. They're not looking at a text editor where you'd see lines of code. They're talking to the AI. They tell the AI, hey, I want a feature that does X. Can you build me a new repository or a new code base where I make a certain kind of application, a new website? Can you go and do research for me? So in the process of building AI, you need to do this research of like, how do you build better algorithms? AI is getting to the point where you can just describe at a high level what you want to happen, and it will go do that software engineering for you. And so to your point, the people in Silicon Valley, they're getting tremendous productivity out of these.
Konstantin Kisin 3:40
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?

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