We’ve had a lot of leaders on The BetaKit Podcast talking about AI recently: as a powerful new tool (like Cohere’s Nick Frosst), or a component of Canada’s sovereignty and prosperity (like AI Minister Evan Solomon). We’ve even had author Cory Doctorow on to discuss what happens after the AI bubble bursts.
“They’re building AI that they’re selling as so powerful that it is exceeding its limitations.”
But we’ve never really discussed the bubble itself.
There are good reasons for this. We’re not economists, and the bubble is so big, growing so fast, and so weirdly shaped that it seems hard to grasp onto and contextualize for healthy debate and discussion. But it can no longer be ignored.
So we’re going to dig in. Helping me to identify and wave a curated selection of red flags in the air is BetaKit managing editor Sarah Rieger.
Keeping a conversation about AI topical and timely is tough sledding. This episode was recorded before Nvidia’s Hugging Face acquisition was confirmed, a whole bunch of (additional) OpenAI executives had departed the company, and a whole bunch of (additional) agentic AI cyberattacks were revealed. It was most certainly recorded before Sam Altman, Dario Amodei, and Elon Musk released statements calling for a slower pace to AI development (although perhaps we have that covered while discussing the merits and likelihood of a managed deflation of the AI bubble).
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That said, the core questions at the heart of our conversation remain remarkably pertinent. What is the current state of the AI bubble? How is it impacting the public markets? And how are the public markets impacting the AI bubble?
Let’s dig in.
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The BetaKit Podcast is presented by CPPO.
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Recorded and edited by Toronto Podcasts.