{"id":5734,"date":"2025-08-24T08:02:00","date_gmt":"2025-08-24T08:02:00","guid":{"rendered":"https:\/\/friscotimes.org\/?p=5734"},"modified":"2025-08-25T08:14:04","modified_gmt":"2025-08-25T08:14:04","slug":"bubble-or-not-the-ai-backlash-is-validating-one-critics-warnings","status":"publish","type":"post","link":"https:\/\/friscotimes.org\/?p=5734","title":{"rendered":"Bubble or not, the AI backlash is validating one critic’s warnings"},"content":{"rendered":"\n

First it was the release of GPT-5 that OpenAI \u201ctotally screwed up,\u201d according to Sam Altman. Then Altman followed that up by saying the B-word at a dinner with reporters. \u201cWhen bubbles happen, smart people get overexcited about a kernel of truth,\u201d The Verge<\/em> reported<\/a> on comments by the OpenAI CEO. Then it was the sweeping MIT survey that put a number on what so many people seem to be feeling: a whopping 95% of generative AI pilots at companies are failing.<\/p>\n

\n

A tech sell-off ensued, as rattled investors sent the value of the S&P 500 down by $1 trillion<\/a>. Given the increasing dominance of that index by tech stocks that have largely transformed into AI stocks, it was a sign of nerves that the AI boom was turning into dotcom bubble 2.0<\/a>. To be sure, fears about the AI trade aren\u2019t the only factor moving markets, as evidenced by the S&P 500 snapping a five-day losing streak on Friday after Jerome Powell\u2019s quasi-dovish comments at Jackson Hole, Wyoming, as even the hint of openness from the Fed chair toward a September rate cut set markets on a tear. <\/p>\n

Gary Marcus has been warning of the limits of large language models (LLMs) since 2019 and warning of a potential bubble and problematic economics since 2023. His words carry a particularly distinctive weight. The cognitive scientist turned longtime AI researcher has been active in the machine learning space since 2015, when he founded Geometric Intelligence. That company was acquired by Uber in 2016, and Marcus left shortly afterward,\u00a0working at other AI startups while offering vocal criticism of what he sees as dead-ends in the AI space.<\/p>\n

Still, Marcus doesn\u2019t see himself as a \u201cCassandra,\u201d and he\u2019s not trying to be, he told Fortune<\/em> in an interview. Cassandra, a figure from Greek tragedy, was a character who uttered accurate prophecies but wasn\u2019t believed until it was too late. \u201cI see myself as a realist and as someone who foresaw the problems and was correct about them.\u201d<\/p>\n

Marcus attributes the wobble in markets to GPT-5 above all. It\u2019s not a failure, he said, but it\u2019s \u201cunderwhelming,\u201d a \u201cdisappointment,\u201d and that\u2019s \u201creally woken a lot of people up. You know, GPT-5 was sold, basically, as AGI, and it just isn\u2019t,\u201d he added, referencing artificial general intelligence, a hypothetical AI with human-like reasoning abilities. \u201cIt\u2019s not a terrible model, it\u2019s not like it\u2019s bad,\u201d he said, but \u201cit\u2019s not the quantum leap that a lot of people were led to expect.\u201d<\/p>\n

Marcus said this shouldn\u2019t be news to anyone paying attention, as he argued in 2022 that \u201cdeep learning is hitting a wall<\/a>.\u201d To be sure, Marcus has been wondering openly on his Substack<\/a> on when the generative AI bubble will deflate. He told Fortune<\/em> that \u201ccrowd psychology\u201d is definitely taking place, and he thinks every day about the John Maynard Keynes quote: \u201cThe market can stay irrational longer than you can stay solvent,\u201d or Looney Tunes\u2019s Wile E. Coyote following Road Runner off the edge of a cliff and hanging in midair, before falling down to Earth.<\/p>\n

\u201cThat\u2019s what I feel like,\u201d Marcus says. \u201cWe are off the cliff. This does not make sense. And we get some signs from the last few days that people are finally noticing.\u201d<\/p>\n

Building warning signs<\/h2>\n

The bubble talk began heating up in July, when Apollo Global Management\u2019s chief economist, Torsten Slok, widely read and influential on Wall Street, issued a striking calculation while falling short of declaring a bubble. \u201cThe difference between the IT bubble in the 1990s and the\u00a0AI bubble\u00a0today is that the top 10 companies in the S&P 500 today are more overvalued than they were in the 1990s,\u201d he wrote, warning that the forward P\/E ratios and staggering market capitalizations of companies such as Nvidia, Microsoft, Apple, and Meta had \u201cbecome detached from their earnings.\u201d<\/p>\n

In the weeks since, the disappointment of GPT-5 was an important development, but not the only one. Another warning sign is the massive amount of spending on data centers to support all the theoretical future demand for AI use. Slok has tackled this subject as well<\/a>, finding that data center investments\u2019 contribution to GDP growth has been the same as consumer spending over the first half of 2025, which is notable since consumer spending makes up 70% of GDP. (The Wall Street Journal<\/em>\u2018s Christopher Mims<\/a> had offered the calculation weeks earlier.) Finally, on August 19, former Google CEO Eric Schmidt co-authored a widely discussed New York Times<\/em> op-ed<\/a> on August 19, arguing that \u201cit is uncertain how soon artificial general intelligence can be achieved.\u201d<\/p>\n

This is a significant about-face, according to political scientist Henry Farrell, who argued in the Financial Times<\/em><\/a> in January that Schmidt was a key voice shaping the \u201cNew Washington Consensus,\u201d predicated in part on AGI being \u201cright around the corner.\u201d On his Substack, Farrell said Schmidt\u2019s op-ed shows that his prior set of assumptions are \u201cvisibly crumbling away,\u201d while caveating that he had been relying on informal conversations with people he knew in the intersection of D.C. foreign policy and tech policy. Farrell\u2019s title for that post: \u201cThe twilight of tech unilateralism<\/a>.\u201d He concluded: \u201cIf the AGI bet is a bad one, then much of the rationale for this consensus falls apart. And that is the conclusion that Eric Schmidt seems to be coming to.\u201d<\/p>\n

Finally, the vibe is shifting in the summer of 2025 into a mounting AI backlash. Darrell West warned in <\/a>Brookings<\/a> <\/em>in May that the tide of both public and scientific opinion would soon turn against AI\u2019s masters of the universe. Soon after, Fast Company<\/a><\/em> predicted the summer would be full of \u201cAI slop.\u201d By early August, Axios<\/a><\/em> had identified the slang \u201cclunker\u201d being applied widely to AI mishaps, particularly in customer service gone awry.<\/p>\n

History says: short-term pain, long-term gain<\/h2>\n

John Thornhill of the Financial Times<\/em><\/a> offered some perspective on the bubble question, advising readers to brace themselves for a crash, but to prepare for a future \u201cgolden age\u201d of AI nonetheless. He highlights the data center buildout\u2014a staggering $750 billion investment from Big Tech over 2024 and 2025, and part of a global rollout projected to hit $3 trillion by 2029. Thornhill turns to financial historians for some comfort and some perspective. Over and over, it shows that this type of frenzied investment typically triggers bubbles, dramatic crashes, and creative destruction\u2014but that eventually durable value is realized.<\/p>\n

He notes that Carlota Perez documented this pattern in Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages<\/a><\/em>. She identified AI as the fifth technological revolution to follow the pattern begun in the late 18th century, as a result of which the modern economy now has railroad infrastructure and personal computers, among other things. Each one had a bubble and a crash at some point. Thornhill didn\u2019t cite him in this particular column, but Edward Chancellor documented similar patterns in his classic Devil Take The Hindmost<\/a><\/em>, a book notable not just for its discussions of bubbles but for predicting the dotcom bubble before it happened.\u00a0<\/p>\n

Owen Lamont of Acadian Asset Management cited Chancellor in November 2024<\/a>, when he argued that a key bubble moment had been passed: an unusually large number of market participants saying that prices are too high, but insisting that they\u2019re likely to rise further.<\/p>\n

Wall Street banks are largely not calling for a bubble. Morgan Stanley released a note recently seeing huge efficiencies ahead for companies as a result of AI: $920 billion per year for the S&P 500. UBS, for its part, concurred with the caution flagged in the news-making MIT research. It warned investors to expect a period of \u201ccapex indigestion\u201d accompanying the data center buildout, but it also maintained that AI adoption is expanding far beyond expectations, citing growing monetization from OpenAI\u2019s ChatGPT, Alphabet\u2019s Gemini, and AI-powered CRM systems.<\/p>\n

Bank of America Research wrote a note in early August, before the launch of GPT-5, seeing AI as part of a worker productivity \u201csea change\u201d that will drive an ongoing \u201cinnovation premium\u201d for S&P 500 firms. Head of U.S. Equity Strategy Savita Subramanian essentially argued that the inflation wave of the 2020s taught companies to do more with less, to turn people into processes, and that AI will turbo-charge this. \u201cI don\u2019t think it\u2019s necessarily a bubble in the S&P 500,\u201d she told Fortune <\/em>in an interview, before adding, \u201cI think there are other areas where it\u2019s becoming a little bit bubble-like.\u201d\u00a0<\/p>\n

Subramanian mentioned smaller companies and potentially private lending as areas \u201cthat potentially have re-rated too aggressively.\u201d She\u2019s also concerned about the risk of companies diving into data centers too such a great extent, noting that this represents a shift back toward an asset-heavier approach, instead of the asset-light approach that increasingly distinguishes top performance in the U.S. economy. <\/p>\n

\u201cI mean, this is new,\u201d she said. \u201cTech used to be very asset-light and just spent money on R&D and innovation, and now they\u2019re spending money to build out these data centers,\u201d adding that she sees it as potentially marking the end of their asset-light, high-margin existence and basically transforming them into \u201cvery asset-intensive and more manufacturing-like than they used to be.\u201d From her perspective, that warrants a lower multiple in the stock market. When asked if that is tantamount to a bubble, if not a correction, she said \u201cit\u2019s starting to happen in places,\u201d and she agrees with the comparison to the railroad boom.<\/p>\n

The math and the ghost in the machine<\/h2>\n

Gary Marcus also cited the fundamentals of math as a reason that he\u2019s concerned, with nearly 500 AI unicorns being valued at $2.7 trillion. \u201cThat just doesn\u2019t make sense relative to how much revenue is coming [in],\u201d he said. Marcus cited OpenAI reporting $1 billion in revenue<\/a> in July, but still not being profitable. Speculating, he extrapolated that to OpenAI having roughly half the AI market, and offered a rough calculation that it means about $25 billion a year of revenue for the sector, \u201cwhich is not nothing, but it costs a lot of money to do this, and there\u2019s trillions of dollars [invested].\u201d<\/p>\n

So if Marcus is correct, why haven\u2019t people been listening to him for years? He said he\u2019s been warning people about this <\/em>for years, too, calling it the \u201cgullibility gap\u201d in his 2019 book Rebooting AI<\/em><\/a> and arguing in The New Yorker<\/em> in 2012<\/a> that deep learning was a ladder that wouldn\u2019t reach the moon. For the first 25 years of his career, Marcus trained and practiced as a cognitive scientist, and learned about the \u201canthropomorphization people do. \u2026 [they] look at these machines and make the mistake of attributing to them an intelligence that is not really there, a humanness that is not really there, and they wind up using them as a companion, and they wind up thinking that they\u2019re closer to solving these problems than they actually are.\u201d He said he thinks the bubble inflating to its current extent is in large part because of the human impulse to project ourselves onto things, something a cognitive scientist is trained not to do.<\/p>\n

These machines might seem like they\u2019re human, but \u201cthey don\u2019t actually work like you,\u201d Marcus said, adding, \u201cthis entire market has been based on people not understanding that, imagining that scaling was going to solve all of this, because they don\u2019t really understand the problem. I mean, it\u2019s almost tragic.\u201d<\/p>\n

Subramanian, for her part, said she thinks \u201cpeople love this AI technology because it feels like sorcery. It feels a little magical and mystical \u2026 the truth is it hasn\u2019t really changed the world that much yet, but I don\u2019t think it\u2019s something to be dismissed.\u201d She\u2019s also become really taken with it herself. \u201cI\u2019m already using ChatGPT more than my kids are. I mean, it\u2019s kind of interesting to see this. I use ChatGPT for everything now.\u201d\n<\/p>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"

First it was the release of GPT-5 that OpenAI \u201ctotally screwed up,\u201d according to Sam Altman. Then Altman followed that up by saying the B-word at a dinner with reporters.…<\/p>\n","protected":false},"author":734,"featured_media":5735,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false},"version":2}},"categories":[6],"tags":[6995,6994,4428,6996,1564],"jetpack_publicize_connections":[],"yoast_head":"\nBubble or not, the AI backlash is validating one critic's warnings - Frisco Times<\/title>\n<meta name=\"description\" content=\"Gary Marcus told Fortune that AI valuations remind him of Wile E Coyote. 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