Could an Alternative AI Save Us From a Bubble?

Over the last couple of years, massive AI investment has largely kept the stock market afloat. Case in point: the so-called Magnificent 7 – tech companies like NVIDIA, Meta, and Microsoft – now account for more than a third of the S&P 500’s value. (Which means they likely represent a significant share of your investment portfolio or pension fund, too.) There’s little doubt we’re living through an AI economy. But many economists worry there may be trouble ahead. They see companies like OpenAI – valued at half a trillion dollars while losing billions every month – and fear the AI sector looks a lot like a bubble. Because right now, venture capitalists aren’t investing in sound business plans. They’re betting that one day, one of these companies will build artificial general intelligence. Gary Marcus is skeptical. He’s a professor emeritus at NYU, a bestselling author, and the founder of two AI companies – one of which was acquired by Uber. For more than two decades, he’s been arguing that large language models (LLMs) – the technology underpinning ChatGPT, Claude, and Gemini – just aren’t that good. Marcus believes that if we’re going to build artificial general intelligence, we need to ditch LLMs and go back to the drawing board. (He thinks something called “neurosymbolic AI” could be the way forward.) But if Marcus is right – if AI is a bubble and it’s about to pop – what happens to the economy then? Mentioned: The GenAI Divide: State of AI in Business 2025 , by Project Nanda (MIT) MIT study finds AI can already replace 11.7% of U.S. workforce , by MacKenzie Sigalos (CNBC) The Algebraic Mind , by Gary Marcus We found what you’re asking ChatGPT about health. A doctor scored its answers , by Geoffrey A. Fowler (The Washington Post) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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Could an Alternative AI Save Us From a Bubble? is an episode from Big Tech by The Globe and Mail.

This episode is 00:53:29 long.

This episode was published on Dec 2, 2025.

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