Let's talk about AI bubbles
Show notes
AI bubble talk is rearing its head again, but the context is very different from the conversations in late 2025.
In this episode of The Deep View Conversations, we unpack the common arguments about an AI bubble and explain why reality naturally falls somewhere in between the doomsayers and AI absolutists.
We look at AI's "Tinker Bell problem": the boom depends partly on people continuing to believe in AI's potential, even as public skepticism grows. Beneath that belief cushion, enterprise contracts drive most of AI labs' revenue, while strong hyperscaler earnings and compute shortages suggest durable demand is building.
We debunk a viral claim that a $200 Claude subscription costs Anthropic $8,000 to serve. We also look at enterprises' push for more control, efficiency and measurable ROI, including one company's claim that some engineers' token use costs 1.5 times their compensation.
Other topics include:
• Training, inference, API pricing and token economics
• Real value, snake oil and the hype cycle
• Why AI demand outruns compute supply
• Why the AI bubble may look more like bubble wrap
• Market rotation into energy and materials
If you're trying to separate durable AI demand from hype and understand where a real correction could begin, then this conversation offers a framework for thinking about what may pop, what may deflate and what may keep growing. Keep in mind that this is industry analysis and not investor advice.
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