Jensen Huang is something of an enigma. The NVIDIA CEO doesn’t have social media and, until recently, rarely gave interviews. Yet he may be the most important person in AI.

Under his leadership, NVIDIA has become a goliath. Somewhere between 80 and 90 per cent of AI tools run on NVIDIA hardware, making it the world’s most valuable company. But unlike his contemporaries, Huang has been remarkably quiet about the technology – and the world – he’s building.

In his new book, The Thinking Machine: Jensen Huang, NVIDIA, and the World’s Most Coveted Microchip, journalist Stephen Witt pulls back the curtain. And what he finds is, at times, shocking: Huang believes there is zero risk in developing superintelligence.

So who is Jensen Huang? And should we worry that the most powerful person in AI is racing forward at breakneck speed, blind to the potential consequences?

Mentioned:

The Thinking Machine: Jensen Huang, NVIDIA, and the World’s Most Coveted Microchip, by Stephen Witt

How Jensen Huang’s Nvidia Is Powering the A.I. Revolution, by Stephen Witt (The New Yorker)

The A.I. Prompt That Could End the World, by Stephen Witt (New York Times)

Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail.

Media sourced from the BBC.

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It was an idea that defied logic: an online encyclopedia that anyone could edit.

You didn’t need to have a PhD or even use your real name – you just needed an internet connection. Against all odds, it worked. Today, billions of people use Wikipedia every month, and studies show it’s about as accurate as a traditional encyclopedia.

But how? How did Wikipedia not just turn into yet another online cesspool, filled with falsehoods, partisanship and AI slop? Wikipedia founder Jimmy Wales just wrote a book called The Seven Rules of Trust, where he explains how he was able to build that rarest of things: a trustworthy source of information on the internet. In an era when trust in institutions is collapsing, Wales thinks he’s found a blueprint – not just for the web, but for everything else too.

Mentioned:

The Seven Rules of Trust by Jimmy Wales and Dan Gardner

A False Wikipedia ‘Biography’ by John Seigenthaler (USA Today)

Machines Like Us is produced by Mitchell Stuart. Our theme song is by Chris Kelly. Video editing by Emily Graves. Our executive producer is James Milward. Special thanks to Angela Pacienza and the team at The Globe and Mail.

Photo Illustration: The Globe and Mail/Brendan McDermid/Reuters

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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)

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