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The sudden AI cooling-off period

Drive down the 280 freeway in San Francisco and you might believe AI is everywhere, and everything. Nearly every billboard advertises an AI related product: “We’ve Automated 2,412 BDRs.” “All that AI and still no ROI?” “Cheap on-demand GPU clusters.” It’s hard to know if you’re interpreting the industry jargon correctly while zooming past in your vehicle.

The signs are just one example of the tech industry’s en-masse pivot to AI, a technology that the executives who have the most to gain from it say will be universe-shifting, inevitable and unavoidable. In California’s tech heartland, every company is now an AI company, just like every company became a tech company sometime in the 2010s.

But just beneath the surface of the breathless promotion of every startup’s AI prowess, cracks are beginning to appear. Some of AI’s biggest boosters, such as OpenAI’s Sam Altman, have warned that investors are overvaluing the potential returns on AI. “Are we in a phase where investors as a whole are overexcited about AI?” Altman said at a private dinner with reporters. “My opinion is yes.”

Altman’s statements coincided with a concession that OpenAI botched the roll-out of the latest ChatGPT model – which he once promised would be a significant improvement over the current GPT 4.5 model.

Sure, Altman’s comments may have been geared at getting investors to consider not investing in his competitors. But there are other signs. Just this past week, a new study from MIT found that 95% of generative AI projects have delivered little to no growth in revenue. And tech stocks of companies with huge AI pushes tumbled this week: Palantir saw a 9% drop in shares, Oracle saw a 5.8% drop, chipmaker Nvidia fell 3.5% and chipmaker Advanced Micro Devices as well as semiconductor designer Arm each saw 5% or more drop in shares. Not even the possibility of lower interest rates, which buoyed stocks in other sectors last week, was enough to turn around tech’s market slide. Even Meta, which had been reportedly spending billions to recruit the top AI talent, announced an AI hiring freeze. Meta sought to downplay the news, with the company’s chief AI officer Alexandr Wang posting on X last week: “We are truly only investing more and more into Meta Superintelligence Labs as a company. Any reporting to the contrary of that is clearly mistaken.”

The sudden AI cooling-off period comes just a week after many of these companies reported largely stellar earnings despite upping their expectation for how many billions they plan to spend on building out their AI capacity over the next few months and years. At the same dinner with reporters, Altman said he expects OpenAI to spend “trillions” on data center expansion in the “not very distant future”, according to the Verge.

While the latest round of AI jitters is being framed as a sign that the AI hype bubble may soon burst, it’s perhaps more of a needed market correction – a reality check for investors who can’t see outside of the Silicon Valley echo chamber. Even former Google CEO Eric Schmidt warns that some of the laser focus on achieving artificial general intelligence – or the idea that AI could at some point match or surpass human intelligence – is misguided.

“It is uncertain how soon artificial general intelligence can be achieved,” reads a column Schmidt co-wrote with China and AI policy lead Selina Xu. “We worry that Silicon Valley has grown so enamored with accomplishing this goal that it’s alienating the general public and, worse, bypassing crucial opportunities to use the technology that already exists.” Schmidt and Xu spend much of the rest of the column boosting the benefits and milestones AI has already met but raise concerns about how the build-at-all-costs strategy Silicon Valley is taking in pursuit of a super intelligent AI is not reflective of the reality for the general public.

“There’s a widening schism between the technologists who feel the A.G.I. – a mantra for believers who see themselves on the cusp of the technology – and members of the general public who are skeptical about the hype and see A.I. as a nuisance in their daily lives,” they wrote.

It’s unclear if the industry will take heed of these warnings. Investors look to every quarterly earnings report for signs that each company’s billions in capex spending is somehow being justified and executives are eager to give them hope. Boosting, boasting about and hyping the supposed promise and inevitability of AI is a big part of keeping investor concerns about the extra $10bn each company adds to its spending projections every quarter at bay. Mark Zuckerberg, for instance, recently said in the future if you’re not using AI glasses you’ll be at a cognitive disadvantage much like not wearing corrective lenses. That means tech firms such as Meta and Google will likely continue making the AI features that they offer today an almost inescapable part of using their products in a play to boost their training data and user numbers.

That said, the first big test of this AI reality check will come on Wednesday when chipmaker Nvidia – one of the building blocks of most LLMs – will report its latest earnings. Analysts seem pretty optimistic but after a shaky week for its stocks, investor reactions to Nvidia’s earnings and any updates on spending will be a strong signal of whether they have a continued appetite for the AI hype machine.

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Certainly! Here are some resources on AI bots and their impact on society: