Our publisher Joe Ragazzo is going to be hosting biweekly YouTube lives with members of our team, on Tuesdays and Fridays. Join him at 1 p.m. ET today for a conversation with editor Nicole LaFond and reporter Kate Riga on the 25th anniversary of 9/11; the start of the NFL season; President Trump’s bribe offer/proposal to give Americans $5,000 if Republicans win the midterms; and Vivek Ramaswamy’s widely-mocked batting cage campaign video.
David Kurtz has a good run-down of the overnight Joe diGenova story in today’s Morning Memo. DiGenova went rogue, then resigned or got fired, then publicly went rogue (essentially claimed that Trump Main Justice wanted to bring evidence-less indictments) and then tried to sort of un-rogue, I guess so as not lose his seat on the Trump gravy/TV hit train. DiGenova is no innocent; he’s a GOP partisan knife-fighter going back to the early ’90s. He made the still-significant shift to team Trump basically at the first opportunity. And here we are.
We’re now flooded with articles about the threat of AI. Here’s another one from the Times op-ed page by a tech journalist, Stephen Witt, who’s written a history of Nvidia, the chip maker powering a lot of the AI boom. Witt describes a few possible approaches to legal intervention. Interestingly, he points to Sen. Bernie Sanders (I-VT) and Rep. Greg Casar (D-TX) as two legislators pitching new laws to get in control of the situation. Casar has a quote that captures it all and illustrates how absent “externalities” are to anything about how we regulate tech: “If the A.I. companies understood that their products have to be safe before they can advance, then they will make the kinds of investments that we need.” Of course, having two left-wing legislators from the party which isn’t even in power as the two guys on the case doesn’t inspire a lot of confidence that anything is going to happen any time soon.
Following up on my previous post, I want to point your attention to this post by Gary Marcus, a highly respected and knowledgable critic/skeptic of AI. You should read it just to get a range of views on this question. The gist is this. He points to two recent warnings. One is the one I describe below in the previous post. The other recently came from a leading mathematician named Terence Tao, who was recently interviewed by Matteo Wong in The Atlantic. Tao warns that the evolution and use of AI is creating a new dynamic in which AI is in the process of shutting down collaboration and information sharing in mathematics and, Tao suspects, soon in the sciences as well. (This part isn’t just asserted. It’s detailed and interesting.) That’s not human extinction, but it’s not great, to put it mildly.
Marcus then turns to the Coxon story. I’ll quote his overview reaction in full.
I happen to disagree with him around timing, and I would argue that Coxon is exaggerating what AI is likely to do anytime soon. But it is nonetheless overall a disconcerting (and plausible) firsthand perspective on the transparently self-indulgent and dangerous thought processes in two of the leading frontier labs
So too alarmist as to time horizons but not implausible and not something to laugh off, either.
You’ve probably seen these reports of an employee of the AI company Anthropic who quit his job and issued a warning on X that suggested AI could, in next few years, escape control and lead to the extinction of humanity. These sound like not just wild but science fiction-type claims. And they’ve lurked around frontier AI labs for years. It’s one of the many weirdnesses of the AI world and those who lead it. The basic pitch: AI is awesome. We need to built it as quickly as possible. Also it might lead to human extinction. Quite an attractive offer! There’s always been a strong sense among many observers that these claims or suggestions or warnings are part of the AI hype machine itself, albeit of a kind of contradictory or paradoxical variety.
But this warning by the ex-Anthropic employee, Jacob Coxon, seems different and is unquestionably being reacted to very differently. That’s the one part of this that is new and real – the reaction to this warning/comment etc is much bigger and operating in the tech, financial and general media. Wired has a good interview with him here. (I think you can read it as a free article if you haven’t read other Wired articles this month.) The gist is that Coxon says it’s imperative to create a regulatory structure, or at least an ad-hoc agreement that can slow the competition between OpenAI and Anthropic, the two most advanced AI engines and research entities. (The inflection point people are focusing on is something called “recursive self-improvement,” which is when this generation of AI model builds the next one.) The problem is that you really need an agreement that brings China into some common framework too. Because they’re in this same hunt, running these same risks, even though I think the common consensus is that Chinese companies are running at least somewhat behind the most advanced U.S. companies. China’s strength has been building models which are only a bit behind the U.S. models but at dramatically lowest costs.
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You’ve probably seen that Treasury Secretary Scott Bessent has now tried to knock down interest rates on US debt – and thus secondarily general rates – with a series of buy backs. But it’s failing. I was actually going to reach out to some economists I know about this because in addition to the real factors – not just momentary crises of confidence – the scale of the interventions seem quite small. $6 billion? In any case, I noticed this update on Paul Krugman’s substack. And he adds something important. Clearly there are an endless list of things Donald Trump has done over the last twenty months or so which would create very rational loss of confidence in the management of the US economy and particularly the US Treasury. But he doesn’t think this is about Trump or falling confidence in US institutions, in large part because the run up is affecting other countries’ borrowing as well. The immediate issue is that there’s only a finite about of money in the world to borrow and the AI build out is taking up enough of it that it’s simply driving up the cost of money. Here’s Krugman’s take.
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