Brendan Foody: prediction

Transcript context

…Awesome. OK, let me shift to talking about the broader labor market here. So there's kind of two parts to this question as we talk about this. One is just how long will we need to do this? Is there a point where we don't need like you guys grew so incredibly fast? Is there a point in like, OK, we don't need humans or we're tapped out. So let's start there and then I'll ask a broader question. So the key question is how long there's going to be things in the economy that humans can do that AI can't do. And I think there's certainly a bucket of people that say, we're going to have super intelligence within three years and humans won't play a role in the economy. And that's one school of thought. Our perspective is very different. Our perspective is that these models are extraordinary and automating a lot of things very quickly. But there's a lot of things that they're horrible at. Like even still, it can't schedule time on my calendar. It can't draft emails for me. It can't use basic tools. And we need evals for everything. for everything that the models can't do, we need evals for the tool use, evals for the long horizon reasoning. Imagine in 10 years when we want models to be able to go out and build a startup for 30 days. We need evals for that to effectively reward it. And I think that That road to improving models will last for as long as there is anything in the economy that humans can do, which models can't, and be a huge portion of what the future of work looks like. And so our mission is creating the future of work. And I think that this is a really exciting industry in giving us a glimpse into the direction that everything is headed towards. There's this tweet that you retweeted that I want to ask you about. If you really think about it, we were put on Earth to create reinforcement learning training data for labs. Yeah. What does that mean to you? What is this person implying? And it's basically what you're saying is we're just helping train models.…

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