AI's Control Problem: Agents, Costs And Robots

AI is moving from answering questions to taking action, and as it spreads, control is becoming the next big fight.

Agents are like teenagers; they're supremely intelligent. They have no fear of fear of any kind of consequence, and you know if you don't put enough guardrails around them, sometimes they might do things that you don't want them to do.

There's really a phase we are seeing is scaling into bankruptcy. The United States deployed 1/10 the number of robots that China did last year. You could get a bill for $50,000 when you thought it was going to be a $20 task. And we, as a country, we've always led these big changes, and we've always

been the owner of the next new platform. And I think it's essential if you want to to be a world power that that you own those things, control over what AI does, over what it costs, and in robotics, control over the industries it's about to reshape. Here's that full conversation.

Hi everyone! It is Thursday, July 30th, and the biggest story in AI this week-it's not a new model. It's that once again, money is starting to matter. Since ChatGPT launched, the industry has operated on a pretty generous assumption: spend whatever it takes now, and the returns will come later. But

every so often, the market tests that assumption, asks whether revenue is catching up, whether demand is real, whether all that infrastructure will actually earn a return-what kind of return? That is what we're watching play out again now. A few of the mega caps have reported so far this earnings

season, and the message is fairly simple. Google showed growth but was punished for the cost. Microsoft was rewarded for showing clearer AI monetization. Meta was punished because the return on its spending remains harder to see. So the AI trade is volatile these days. Nothing captures that better than what

just happened to Leopold Ashenbrenner. If you don't know Leopold, he is the former AI Open AI researcher who wrote Situational Awareness, basically the definitive Super Bowl case that AI progress is about to go vertical. He then built a hedge fund around that worldview, and it reportedly grew to more than

$20 billion in just about two years. Today, we learned that after getting hammered in the recent AI sell-off, the fund sold its public stock portfolio to Citadel. The Financial Times puts that book at roughly 16 billion dollars and called it one of the largest rushed stock transactions in Wall Street

history. Now situational awareness is holding on to its private investments, including an anthropic stake, but the public trade is now in Ken Griffin and Citadel's hands. And in a nice bit of timing, chip stocks they are ripping today.

That could change tomorrow, but more importantly, it shows why the Citadel sale doesn't settle anything about the underlying AI thesis. May tell us more about leverage, timing, liquidity. You can be right about where the technology is going and still get forced out of the trade before it gets there. At the

same time, Dwarkes Patel has been making an interesting point about the chips themselves. A lot of the bearish AI math assumes that these GPUs they age like iPhones. Nvidia releases a new generation; the old one becomes less useful, and big tech has to start replacing hundreds of billions of dollars