All-In with Chamath, Jason, Sacks & Friedberg
Inside America's AI Strategy: Infrastructure, Regulation, and Global Competition
23 Jan 2026
Chapter 1: What is the current state of America's AI infrastructure?
Great to see everyone, and I'm thrilled to be able to talk about the issue of the day, and that is artificial intelligence and AI in our world. David, Michael, I'd love you to talk about where we are right now in terms of the pursuit to be the number one lead AI country. How are we doing, David?
I think we're doing great. Maria, last year, President Trump gave a major AI policy speech just in July, and he declared that the United States had to win the race. He he first of all declared that we were in one. And I think his speech was reminiscent of when President Kennedy declared that we were in a space race and had to win that race.
I think since then, what you've seen is that American companies have only innovated more. You're seeing all sorts of really incredible products being released all the time. I think that American AI models, chips. Data centers only just keep getting better and better. So I feel very good about the American position in this ARA.
Chapter 2: How is AI expected to impact various sectors?
Certainly, we have some very competent and formidable competitors. China, obviously, has a lot of very smart people working in this area. But I do think that just what you see from American companies in Silicon Valley right now is really incredible.
And yet there are still so many questions about all of the spending underway to build this out with regard to data centers. And of course, the question keeps coming up, are we spending too much? Will we get the return on investment? How do you see that?
I think that we will. I think that the reason why you're seeing this huge infrastructure build out is because the demand is ultimately there. I know a lot of people worry about whether this could be like a dot-com situation.
Chapter 3: What are the implications of China's AI strategy for the U.S.?
Remember where we had the whole fiber build out in the late 90s, then we had a dot-com crash. The difference here is that in the late 90s and early 2000s, we had a problem known as dark fiber, where you had this fiber build out and then it didn't get used. There's no such thing as a dark GPU right now.
Every GPU that's being put in a data center is getting used, and it's being used to generate tokens, and that's to power this new generation of AI chatbots or coding assistants. And there's just been some releases in the last couple of months on the coding front that, you know, if you're following what software developers are saying, They're saying it's mind blowing.
It's completely revolutionizing their industry. So demand for tokens just increases and that increases the demand for this data center build out that we're seeing. So I don't think it's going to stop anytime soon. And just last year, this infrastructure build out added about two percent to the GDP growth rate. And I think that's what helped propel us to this four to five percent growth rate.
And I think you're going to see something similar this year.
Well, it is certainly leading growth, Michael. And I'm so happy to be able to get this conversation going with both of you who are really leading this. David, thank you. And Michael, thank you. Same questions for you, Michael.
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Chapter 4: What is America's outlook on AI entrepreneurship?
Assess where we are right now on AI. group, for those who haven't been tracking as closely as we do every day, the plan really had essentially three pillars. And it talked about how, one, how can the U.S. continue to out-innovate our competitors? Two, how can we drive the infrastructure build that we need to support this AI revolution?
And three, how do we actually share with the world or export our great American technology? And For each of those three pillars, there was quite a lot of actions that the federal government has taken to drive that forward. And I think we're pretty proud to say that we've made, I think, pretty good progress on all three.
Just focusing a little bit on the innovation we were talking about earlier, I think the core insight that we've always had about how you drive this innovation is you have to have a regulatory environment that allows this technology to be developed and ultimately commercialized in the United States. And the U.S. has done a great job
compare it to the rest of the world on sort of setting that up and creating a framework that works, but we could always do better and improve it. And the president in his speech in July talked a lot about this issue of a patchwork of state regulations and how can we ensure that there aren't 50 different rules around AI.
And what's most important about this debate, which I think a lot of people sometimes don't sometimes miss, is The patchwork is actually most detrimental to early stage young companies and entrepreneurs.
If you want to develop a new AI technology, if you want to build something on top of one of our great frontier models, having to figure out how to navigate 50 different rules across 50 different states creates a lot of friction.
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Chapter 5: How is the U.S. addressing regulatory challenges in AI?
And ultimately, the big guys are the ones that can succeed in that environment the best. So we're spending a lot of time trying to think about how can you create a legislative proposal that can actually deliver on a sensible national framework to solve this regulatory issue.
So what would you say then, Michael, are the basic frameworks that are sort of must have in that kind of federal oversight? Because some states did push back in the U.S. and say, no, no, no, we want to be able to control our destiny when it comes to AI. What's most important when you look at that framework in terms of a federal oversight?
Yeah, I think in the executive order the president signed in December directing us to kind of work through this proposal, he listed a few things that the state should continue to be able to pursue individually on their own. Legislation or rules around child safety was on that list.
The rules around permitting of data centers and build outs are continuing to be something that states should look at. So there are a few things that were enumerated, but that's the kind of stuff that I guess Dave and I are going to be working through. I don't know if you have any thoughts on that.
Yeah, I mean, I think the basic problem that we have is that, I mean, frankly, the states are going hog wild right now with regulation. There's over 1,200 bills going through state legislatures right now. I think it's very much a knee-jerk reaction.
I know there's a lot of fears and concerns about AI, but it seems like for every hypothetical concern, there's multiple state bills now to try and regulate that thing before we really know how it's going to play out. And I think it would be
better to, I think since this technology is so new and the environment is so dynamic, I think it'd be better to spend a little bit more time studying how AI is actually being used and what risks are actually materializing before you over-regulate the thing. But in any event, that's what we're seeing right now at the state level.
And I think that the president's been very consistent that it would be better to have one rule book, a single rule book at the federal level, lightweight federal standard. I think this problem is only going to get more acute over time because, again, as you have 50 different states running in 50 different directions, the patchwork problem only gets more significant.
So in any event, this is something that we're going to work, I think, closely together on this year, which is to see if we can get enough consensus on a federal framework to enact a law. Only Congress can ultimately cramp the states. We understand that. And, you know, as you know, it's very difficult to get a bill through Congress.
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Chapter 6: What are the potential risks of over-regulation in AI?
You need 60 votes in the Senate. It has to be bipartisan to to a certain degree. So but we're going to try and see if we can work to get that consensus.
Yeah. And do you have any clarity on the timing on that in terms of support in Congress for a federal oversight? Or do you see pushback there as well, depending on the state you're talking about?
Well, there's pushback in Congress to the idea of preemption without a federal standard. So in other words, you can't replace something with nothing. This is sort of the thing that we heard repeatedly. But I think there is quite a bit of interest in both the House and the Senate towards having, again, some sort of lightweight federal standard.
But we're still in the early stages of those conversations, and we're going to see what we can try and get done this year.
Meanwhile, you've got some people pushing back after wanting to see the innovation and growth of data centers. Now they're saying, not in my backyard. What about that? Is that an issue?
Yeah. I mean, we got a letter recently from Bernie Sanders saying, stop all data centers, all data center development. And if we do that, we will lose the AI race. I mean, you do need this infrastructure. Other countries are building out this infrastructure. China's building out. I think they're spinning up a new nuclear power plant or coal plant, new energy every single week.
And a lot of that is going to power their data center. So it would fundamentally, I think, cripple the United States in the AI race if we just stopped building data centers altogether. At the same time, there are concerns about affordability, about whether consumers would have to pay a higher electrical rate because of data centers.
President Trump's been really clear that consumers should not have to pay higher rates for electricity because of data centers. You saw just last week Microsoft stepped up and made a pledge. that its data centers will not cause residential rates to increase, I think you'll likely see other tech companies stepping up and making similar commitments.
And in fact, when I've talked to the hyperscalers and when I've talked to the AI companies, it was never their plan to draw off their grid. They all saw standing up their own power generation as part of their build-out. And what Secretary Wright, our Secretary of Energy, has been doing is trying to
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Chapter 7: How is AI transforming industries like healthcare and automotive?
The result of that is, you know, A, we get this infrastructure, B, residential rates don't go up.
Yeah, because Michael, this race has fast become, it's moved from an AI race to a power race.
And I think what we're seeing is that we need to share a good story about how ultimately this build out is going to be net positive for American rate payers. And I think sometimes if you're in a small community and someone shows up to build a data center, I mean, you have to make it clear that ultimately this is something that's going to actually lower your rates long term.
And the president put out a truth last Monday where he was, as David said, very clear that, you know, if you're going to build a data center, you have to pay your own way for it. And Microsoft has stepped up. And our hope is that many others will do the same.
But some companies, because they don't have the cash right now, are borrowing money, right, to build out the data centers. And there's also a worry that the banks will be left holding the bag for some of this because, again, the spending is too much. Your thoughts on that?
Well, I think there is obviously that concern. I mean, you know, I think it's less, I would say, the banks and more. You see Oracle making a huge investment. You see Blackstone making huge investments, real estate companies. Ultimately, I think these are very savvy market players, very deep pocketed companies, and they're doing this because they see an ROI there at the end of the rainbow.
Can I just make one other point about just the data centers? So just on electricity, I actually think that if we allow the data centers to stand up their own power generation, it will actually bring down rates. Not only will it not increase residential rates, it'll bring it down.
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Chapter 8: What future breakthroughs in AI should we anticipate?
And it'll do that in two ways. One is that the data centers can give or sell power back to the meter when they have excess. So that will help bring down rates. Second, there's a lot of fixed costs involved in power generation. It's not all variable. So when you're able to amortize those fixed costs over a greater supply, you bring down the meter rate for everybody.
And so there's huge economies of scale. So the more scale you get in electricity, like most other things, the price comes down. So it's actually a good thing that the that we have this build out going on because it will ultimately reduce prices for consumers. But we do have to make sure that these new data centers aren't just plugging into the grid and using they have to be contributing back.
And I think what a great policy change has made under this administration, the Biden administration had, as a matter of policy, had made it such that you couldn't do this behind the meter energy generation. If you wanted to bring your own power, you couldn't. You had to be part of the larger grid. So I think that rule has changed by Secretary Wright and by FERC to kind of allow this to happen.
And I agree with David. I think once you have sort of greater scale in the power generation, you'll be contributing back into the grid in a way that benefits ratepayers.
Let's go back to the uses and how AI is changing our lives. You mentioned earlier all of the uses and the impact that AI is having. What do you see as the most important use and where AI is being deployed and implemented best right now?
Well, it's interesting. I think there's been an evolution. So I think we started with AI chatbots like ChatGPT. And in a sense, that was kind of like better web search. It was really great for research. You could ask it questions and give you answers to anything. Then we saw models at Chain of Thought, and they could start to do deeper reasoning. Then we saw coding assistance.
And I think over the past few months, there's been a real breakthrough. If you talk to people, software developers, it really seems like there's been a major shift and just improvement in the quality of the coding assistance. And I think where that's going next is tools for knowledge workers. So the same types of assistants that have been outputting code can now output any type of format.
So whether it's like Excel models, PowerPoints, websites, you name it, knowledge workers are now going to be able to generate all these different types of things the same way that software developers have been using AI to generate code. I think that's one of the big things we're going to see in 2026 is again, this productivity boom for knowledge workers.
So I think that's like one of the things you're seeing on the ground. And then separately, there's a bunch of things happening in industry verticals. So different industries being impacted by AI. So in healthcare,
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