Markets Shudder Despite Nvidia's Bullish Outlook, Signaling Rising Risk
Plus, big shifts in key AI alliances show Google coming on strong
The Week in Short
Jensen Huang’s AI exuberance not enough for Wall St. Crypto losses reach $1 trillion. Index, Sequoia see potential returns shrink as IPOs give back gains. Anthropic’s promiscuous alliances show Google’s strength. AI applications give Europe hope. Jeff Bezos enters the foundation model race with Project Prometheus. Lambda & Luma AI lead big funding week. Meta antitrust win could boost M&A. AI giant Yann LeCun & VC marketing star Shernaz Daver move on. Trump targets state AI regs. Cook, Benioff celebrate MBS at the White House as Trump insults murdered journalist Jamal Khashoggi.
Even Jensen Huang & AI Can’t Juice Equities Forever. Crypto Underscores the Uncertainties Ahead.
After months of unsettling but contradictory indicators, the markets this week sent a pretty clear signal that the long AI-driven run-up is over. We’re not going to say that a bubble is bursting — regular readers know that we don’t find the B-word to be a very helpful moniker — but soaring public equity markets can no longer be counted on to drive tech valuations.
With private markets now the new public markets, that has implications for all investors.
A lot of risk gauges are flashing red.
The week began with the S&P posting a four-day losing streak, its longest in a while, only to be rescued for a moment by Nvidia’s spectacular earnings. Yet even though the AI bellwether’s forecast was as bullish as they come, stocks on Thursday quickly resumed their slide — suggesting there is no kind of good news that will shift market sentiment anytime soon.
Big increases in corporate VC investing, exemplified by Nvidia’s aggressive moves to finance its customers, tend to signal a market top, per an interesting piece from Reuters. That’s even aside from the question of whether it’s distorting the picture on underlying demand.
Bitcoin’s slide is accelerating; you know there’s trouble when its defenders resort to talking about “fundamentals.” This wouldn’t have mattered much outside of crypto circles a few years ago, but it now poses problems for a range of investors. The crypto-treasury trade, which gave rise to publicly traded companies whose only business was owning crypto, is probably done for good. And the vaporization of $1 trillion in paper wealth will surely have ripple effects.
Private-credit markets, which have been taking a lot of the lending business once controlled by big banks and have been central to the AI data center build-out, are bracing for defaults. Relatedly, debt-heavy companies like CoreWeave are seeing their stocks sink.
The burst of IPOs earlier this year seemed to be laying the groundwork for investors to get some liquidity from the over-valued unicorns minted in 2021 and 2022. That is now in doubt, especially in light of the correction in the big IPO run-ups of the spring and summer. (More on that below.)
There are a few caveats here. Some of the sell-off is surely due to signals that the Fed will not in fact deliver another interest-rate cut this year. Consumer spending and the job market appear to remain resilient. The major AI companies show few signs of pulling back. Big Tech earnings continue to be extraordinary by any historical measure. The big promise of AI, measured by consumer uptake, revenue growth, and enterprise enthusiasm, remains intact.
But this moment is a reminder of a lesson learned many times before: new technologies that fulfill their promise of changing the world usually create many epic fortunes — and sometimes epic losses too.
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VC IPO Gains Lose Some Luster as Shares Fall
The market downturn has erased billions in value for some of Silicon Valley’s most influential investors as recent IPOs give back gains.
Index Ventures, the largest shareholder in Figma, has seen the worth of its 62.7 million shares in the design-tool company fall from $7.2 billion the day after the late July IPO to about $2.1 billion as of the Thursday close.
DST Global, the biggest outside backer of Chime with 52.3 million shares ahead of the IPO, has seen its gains fall by about half as shares dropped to $17.95 Thursday from $37.11 on opening day back in June (it’s unclear how much DST Global sold, if any shares, during the IPO).
Sequoia Capital’s 76.99 million shares in Klarna have likewise dropped in value from $3.5 billion to about $2.16 billion since the IPO two months ago.
To be sure, the investments remain big wins for the firms, even if they didn’t win even bigger from dramatic post-IPO run-ups that few anticipated. At CoreWeave, which barely got its IPO out the door, Magnetar Capital’s 107.96 million shares have climbed from $4.3 billion at the first-day close to $7.47 billion Thursday — well below the post-IPO peak, but still far above the debut price.
Partnership Politics
As AI Alliances Shift, Google Seizes the Pole Position
When OpenAI announced in early November that it had signed a major cloud-computing deal with Amazon, the significance went well beyond the dollar figure. Sure, $38 billion was impressive, but the real message was that the industry’s AI alliances were in flux.
It’s evident we’ve entered a new phase of the foundational model wars, where no frontier lab is beholden to any single cloud giant. Indeed, the labs themselves are now competing with them by building their own data-center capacity.
Nowhere was the shift more apparent than at Amazon. The company has invested $8 billion in Anthropic and Jeff Bezos himself internally discussed it as Amazon’s big AI bet, according to a person familiar with the matter. It wasn’t their only one — Amazon has invested in its own frontier model, called Nova — but bringing OpenAI onto AWS has made the Anthropic relationship look like one of many, rather than a special partnership.
Some Anthropic executives on the infrastructure side were concerned that the Amazon-OpenAI deal could deprive them of some AWS resources, sources told us. A couple weeks later Anthropic announced a deal with Microsoft — once OpenAI’s exclusive provider — wherein the tech giant would invest $5 billion into Anthropic, and Anthropic would in turn purchase $30 billion of Azure compute.
Microsoft is now empowering the ChatGPT maker’s largest rival. And Anthropic, which had long worked with multiple cloud providers, is now pushing even farther in its quest for more capacity.
Anthropic also deepened its partnership with Google, securing “tens of billions of dollars” in cloud computing. Though that deal, which will provide Anthropic with one million of Google’s tensor processing units (TPUs), was struck over the summer, Anthropic only announced it in late October — a week before the AWS-OpenAI tie-up became public.
Beyond expanding its computing capacity, Anthropic intended the stepped-up Google partnership as a recruiting signal, another source said. In the war for AI talent, declaring that you’re about to scale up your compute budget is catnip to researchers, whose loyalties often follow the biggest chip clusters. With each OpenAI infrastructure announcement grabbing headlines, Anthropic wanted to signal that it’s keeping up
There’s delicacy to all this; in the press releases for the Google and Microsoft deals, Anthropic took care to note that Amazon remained its “primary training partner and cloud provider,” and that the two companies continued to work together on big AI-chip build-outs.
In this landscape, the company that looks the most formidable is Google. A few years ago, the media loved to slam it as a company that was drowning, dragged down by a wayward corporate culture and poor leadership. Sundar Pichai seemed to have whiffed on large language models (a technology Google had partly invented!) and looked like he might be on the ropes.
Now Google is storming back. Its stock is up 75% in the past six months, trouncing every major tech company — that’s more than double Nvidia’s gains — and its market cap is neck and neck with Microsoft’s.
Google is the only fully verticalized tech giant, with each part of its stack at or near the top of the class. Its TPUs are the only strong rival to Nvidia’s GPUs for training and inference (Amazon’s in-house chips don’t have a great reputation), its data center footprint is large and expanding, and its Gemini 3 model is currently state of the art, according to the AI benchmarks (Sam Altman even tipped his hat to Gemini and in private has reportedly told colleagues Google’s rise will cause OpenAI turbulence).
There’s a precedent for this kind of upstart-versus-incumbent dynamic. At the dawn of the streaming wars, Netflix’s then content chief Ted Sarandos used to say that his goal was to “become HBO faster than HBO can become us.” In AI, the dynamic runs in the opposite direction. OpenAI has been trying to become Google faster than Google can become OpenAI. The problem for OpenAI is that Google is managing to become both.