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Episode publishedPodcast: All-In with Chamath, Jason, Sa...All-In with Chamath, Jason, Sacks & Friedberg
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Alright, everybody. Welcome back to the number one podcast in the world, the all in podcast. With me again, the core four, the original quartet, David Sacks, David Friedberg, Chamath Palihapitiya. I'm Jason Kalakanis, and we have a very full docket today. Alright. Topic one, gentlemen, AI acceleration. It was a big week for AI. New study published on Monday, February 9 in the HBR, Harvard Business Review, suggesting that AI tools intensify work but do not reduce it. Two UC Berkeley researchers spent eight months embedded at a 200 person tech company. So this is one company's experience. What t
Alright. Well, a few points here. Number one, as you may recall on the prediction show for this year, my most contrarian belief is that AI would increase demand for knowledge workers, not put them out of business. And I think you see in this UC Berkeley study the reason why that might be the case is because the employees who use these tools, like you said, they worked faster, they took on a broader scope of tasks, they actually ended up working more hours in the day, so they did more work, not less, and even more effort rather than less. Not because they were required to, but just because they
Couldn't concur or agree more. Nick, throw up that tweet I did. I I did a tweet, and it got 2,000,000 views. Basically, said, listen. If you got laid off by Amazon or Microsoft over the last two years, just learn OpenClaw and automate your previous job, show you know how to use these tools, go back to your boss and say, hey. I wanna come back and automate everything or go to startups. Every startup I know is hiring for this position, which is somebody who knows how to build and manage agents. There is no job rec for this yet or a title. We should come up with what this person does, but it it u
I think there are two open questions that I find really interesting right now. The first question is I tweeted it this morning, but is on prem the new cloud, which is weird to think that that could even be possible. But we've spent since 2008 migrating everything to cloud because there were these economies of scale, and it created better margin and lower OpEx and lower CapEx because you could essentially share infrastructure with other companies. And that's how AWS and GCP have built such gargantuan businesses. The counterpoint to that, though, is that in the AI revolution, companies, I suspec
Good insights there. And I have some thoughts on the on prem because I'm actually doing it right now. Friedberg, your thoughts on this moment in time when we have people saying it's happening faster and it's become recursive. Recursive, obviously, fancy word for those in the audience who haven't heard it before. Just these models and these agents can go out and improve their own work. So after they do some work or a job for you, you can have another agent say, hey. Here's how to do it better or go learn these new skills. Go use this skill last thirty days to go find the last seven days or thir
Well, I think the thinking historically was that it was gonna be about recursive model development where we were gonna continuously improve the actual model, and we were waiting for a context window where you could feed the model back to itself. So you're effectively retraining the model continuously. And it may be the case that the output is with recursive, and that turns out is having the effect that everyone was waiting for. So it's kind of a surprise. I saw a lot of computer scientists that have worked in AI for some time, I think, be a little bit surprised about this moment that we're in,
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