Is the AI industry racing towards a point where the tech’s progress stalls out or slows to a crawl? Many experts, including one of the field’s foundational figures, seem to think it’s possible.
“There is a clear possibility that we will hit a wall, that there’s some difficulty that we don’t foresee right now, and we don’t find any solution quickly,” Yoshua Bengio, one of the “godfathers” of AI, told The Guardian.
“And that could be a real [financial] crash,” he added. “A lot of the people who are putting trillions right now into AI are also expecting the advances to continue fairly regularly at the current pace.”
Part of the problem is that the AI industry has hyped itself into an impossibly high-stakes situation. AI finding some niche uses in some industries is not the premise that has raked in trillions of dollars in investment; instead, the end game is creating a so-called artificial general intelligence, or AGI, a hypothetical AI system that matches or surpasses human cognition. David Cahn at the powerful Silicon Valley investment firm Sequoia Capital said as much in an October blog post quoted by The Guardian: “Nothing short of AGI will be enough to justify the investments now being proposed for the coming decade.”
Betraying the vagueness of the AGI mission, the more specific points of what constitutes AGI is hotly debated, and some tech leaders, including OpenAI CEO Sam Altman, have begun distancing themselves from the terminology. Mark Zuckerberg’s Meta, for example, favors calling it — whatever “it” is — an AI “superintelligence” instead.
Concerns over an AI “wall” or “winter” popping an AI “bubble” have been raised since the boom kicked off three years ago, and were rekindled last summer with the disappointing launch of OpenAI’s GPT-5 model, which saw only marginal benchmark gains over its predecessor, and which many fans felt was subjectively worse to talk to.
In November, some faith in the industry was restored, however, with the launch of Google’s Gemini 3 models, as well as Google’s new video generating models capable of producing stunningly lifelike footage. For the time being at least, doubts over the industry’s future were offloaded onto doubting OpenAI’s ability to lead it instead, with Google taking up the banner.
Regardless of who’s at the helm, the stakes are enormously high, as the rapid buildout of AI data centers is projected by Morgan Stanley to soar to $2.9 trillion by 2028, with Meta alone saying it will spend $600 billion on US infrastructure.
Much attention has begun to be paid to the “circular” nature of the deals being struck among major AI players, such as AI chipmaker Nvidia pledging to invest up to $100 billion in OpenAI, while OpenAI agrees to buy billions of dollars worth of Nvidia’s AI chips. The fear is that these deals are helping prop up a multi-trillion-dollar house of cards that could catastrophically collapse if investors get spooked by an AI wall.
In some cases, the calls are coming from inside the house. Meta’s recently ousted chief AI scientist and fellow “godfather” of AI Yann LeCun is a vocal skeptic of the large language model architecture used to power the industry’s leading chatbots, believing an entirely new form of AI “world” model, which is trained on physical data instead of just language, is the pathway to building truly advanced AIs.
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