Chapter 1: What is the main topic discussed in this episode?
This is Andrew Ross Sorkin, the founder of Dealbook. Every year, I interview some of the world's most influential leaders across politics, culture, and business at the Dealbook Summit, a live event in New York City. On this year's podcast, you'll hear my unfiltered conversations with Gavin Newsom, the CEO of Palantir and Anthropic, and Erica Kirk, the widow of Charlie Kirk.
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From The New York Times, I'm Natalie Kitro-Eff. This is The Daily. After years of soaring optimism and massive investment in the AI boom, in recent weeks, Wall Street has begun to seriously question whether that optimism was overblown and whether we're actually in a bubble that may soon pop.
And yet, despite all that hand-wringing, Silicon Valley has only doubled down, projecting total confidence about the hundreds of billions of dollars it's pouring into the technology. Today, my colleague Cade Metz explains why. Why tech companies believe so fervently in AI. Why they're willing to take huge risks to deliver on its promise. And whether that bet could backfire.
It's Thursday, November 20th. Cade, it seems like the conversation on Wall Street, among investors, in Silicon Valley, even in Washington these days, has gone from whether we're in an AI bubble to the general sense that, yes, we probably are in some sort of a bubble. And yet the companies that you cover from your perch in Silicon Valley, they're continuing to spend huge amounts of cash on this.
So explain to us, what is their justification for spending all this money?
Well, three years after the arrival of ChatGPT, the open AI chat bot that really started this AI boom, this is clearly a powerful and in some ways transformative technology. It's used not only to search the Internet in new ways, it can help people do specific tasks in a faster and more efficient way than they did in the past. You see businesses adopting services that can transcribe meetings.
You see other applications in health care. There are ways that this technology is already changing the way we live and the way we work. And these companies, and this is classic Silicon Valley, see much bigger transformations on the horizon.
These are people, executives, these titans of industry are looking not just at what is possible today, but what they think this technology will do in the future.
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Chapter 2: What is the current sentiment on the AI market bubble?
It seems kind of hard to get your head around. Like, what does it mean, actually, Cade?
It's shorthand for a machine that can do all of the economically valuable work that people like you and I do on a daily basis. They want to essentially replace all human workers. They want to give the world a technology that can do any job. That, in theory, is worth all this spending. But it's worth saying that we don't know how to get to such a goal. That is a lofty thing to reach for.
But so many Silicon Valley executives remain undeterred.
Mark Zuckerberg, CEO of Meta. I would guess that like sometime in the next 12 to 18 months, we'll reach the point where like most of the code that's going towards these efforts is written by AI.
Jensen Wang, the CEO of NVIDIA.
If there's one thing that I would encourage everybody to do is to go get yourself an AI tutor right away. We're going to become superhumans because we have super AIs.
They are all making the case that this spending makes sense. The poster child of this attitude is Sam Altman, CEO of OpenAI.
There are not many times that I want to be a public company, but one of the rare times it's appealing is when those people are writing these ridiculous OpenAI is about to go out of business and, you know, whatever. I would love to tell them they could just short the stock and I would love to see them get burned on that.
He has told the rest of the world to bet against his company at their own risk, and he continues to flaunt the company's spending. He and the rest of the industry are all in.
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Chapter 3: Why are Silicon Valley companies investing heavily in AI despite risks?
There are famous examples of this, and that's often what people think of. But underneath that, And this is where the analogy really holds up to today.
As those startups were being built, there were other companies that were building the infrastructure needed to drive the internet, that were spending enormous amounts of money to lay the fiber optic cable that would carry all that information across the internet to our machines. When the bubble burst, a lot of those companies went bankrupt.
And that's often what people are thinking about as they look back at the dot-com bubble.
Meaning there's a fear that the companies that are laying the fiber optics of the AI revolution, which is, you know, the analogy would say these data centers that are housing all of these chips, that those companies could go under. That's the fear.
Yeah.
Just like then, you have companies spending enormous amounts of money on the infrastructure needed to drive on this. The difference is they are spending a lot more today than they did 25 years ago.
But I'm struck by the fact, Cade, that obviously the dot-com bubble, it burst, but there were many, many winners, right? I mean, we still have, as you said, a lot of these companies that were born in that era. So what's the takeaway there?
This is a great point. So many of the applications that were promised by all those startups that went out of business are part of our daily lives today. Amazon delivers our pet food. Other companies deliver our real-time products. Internet video, so many of the things that were promised in we have today.
And we're actually using that fiber optic cable that was laid and that sat there dormant for many years. And we are now reaping the benefits. It's just that it didn't happen as quickly as a lot of people thought.
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Chapter 4: What is the significance of spending billions on data centers?
As we think about this moment, we need to realize the realities of this technology. It is very powerful in many ways. Healthcare being perhaps the prime example, drug discovery. We are on the path towards some amazing things. At the same time, we're on the path towards some things that are concerning.
If things don't progress at the pace that Silicon Valley says, this could cause problems across the larger economy, as we talked about. But it might give us the time we need to continue to think about all the big questions that hang over this technology and that hang over our future. it might give us time to prepare for that future.
Well, Cade, thank you so much.
Glad to be here.
On Wednesday afternoon, NVIDIA announced that in the most recent quarter, its profit was $31.9 billion, up 65% from a year ago. And it reported record sales. The news buoyed its shares in aftermarket trading and was seen as a sign the jitters on Wall Street over AI had been calmed. At least for now. We'll be right back. Here's what else you should know today.
On Wednesday, President Trump announced on social media that he'd signed legislation calling on the Justice Department to release its files on Jeffrey Epstein within 30 days. But Trump's signature doesn't guarantee the release of all the files. The bill contains significant exceptions, including a provision that allows records to be withheld if they jeopardize an active federal investigation.
Last week, Trump demanded that the Justice Department launch an investigation into Democrats mentioned in some of the files, and Attorney General Pam Bondi said she'd started one. That could give the administration another reason to withhold documents.
And in a remarkable hearing on Wednesday, a federal judge grilled government prosecutors pursuing charges against former FBI Director James Comey, revealing serious vulnerabilities in their case. In response to the judge's questioning, Lindsay Halligan, the U.S.
attorney handpicked by Trump to bring the case, admitted she'd never shown the second and final version of the Comey indictment to the full grand jury before the foreperson signed the charging document. Comey's lawyers immediately seized on that irregularity, saying it justified dismissing the case entirely.
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