3 August 2026
13 new episodes (10 hours listening) published by the 38 podcasts on the list. 6 highlight clips below (15 mins total).
Investment 3 August 2026 · 6 clips
Big Technology Podcast
David Cahn
A partner at Sequoia Capital, per the episode description. He wrote the AI's $200 billion question posts from 2023 onward, says he has been investing in AI for about ten years having started a year after the Transformer paper, and meets roughly 300 young people a year on talent.
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1 of 2 contrarian
David Cahn argues the market underprices both the chance of AGI and the chance of a reckoning, and overprices the world where the present arrangement simply continues.
The middle case has hyperscalers renting out GPUs at accelerating revenue with no new business line behind it, which runs into negative free cash flow and cannot hold. He hangs the whole split on whether any application follows coding, and if one arrives the state he calls unsustainable is just the business.
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2 of 2 framework
David Cahn calls the hyperscaler capex boom a resource curse: they build the data centre, then invest in the customer who will pay them rent for it.
The cloud oligopoly throws off cash faster than any of the three can deploy it elsewhere and each has to match the others, so the spending follows from what they hold rather than from an outcome they are steering toward. He would run Google's chip line as a merchant business against Nvidia instead of keeping every TPU in-house.
Alpha Exchange
EPISODE 264: The Market Disregards Correlation
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1 of 2 contrarian
Dean Curnutt argues the AI trade's overlapping loans, backstops and equity stakes create a shared exposure that realised correlation cannot see, which is exactly why index volatility is so low.
Nvidia and Google recently ran a one-month realised correlation around minus 10% while stocks and long Treasuries ran plus 71, so the estimator that anchors implied correlation is reading the wrong signal. His claim is that the common funding arrangements bind together in a shock and the price handicaps none of it.
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2 of 2 explainer
Dean Curnutt walks through a Hong Kong leveraged ETF on SK Hynix that reached 14 billion dollars, breached its own 25% options limit, and ran call-to-put open interest near 100 to 1.
Deep in-the-money calls leave the dealer short gamma, so the hedge had to be dumped into a falling market, while daily rebalancing forced buying on the way up and selling on the way down. He then reads the same structure straight across to Micron, SanDisk and SOXL, the semiconductor fund peaking near 100 billion dollars of exposure.
AI 3 August 2026 · 6 clips
Big Technology Podcast
David Cahn
A partner at Sequoia Capital, per the episode description. He wrote the AI's $200 billion question posts from 2023 onward, says he has been investing in AI for about ten years having started a year after the Transformer paper, and meets roughly 300 young people a year on talent.
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1 of 2 explainer
David Cahn puts the cumulative bill AI has to pay back since ChatGPT at roughly $3 trillion, against the $200 billion he was asking about in 2023.
Cahn derives it from a dollar of energy for every dollar of GPU, then a 50% margin for whoever runs the data centre, which puts required lifetime revenue at about four dollars for each dollar Nvidia sells. He insists the yearly figures stack rather than replace each other, and 2027 is not in the total yet.
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2 of 2 contrarian
David Cahn says two years of evidence has not shown that owning the data centre produces a better model, and that inside a hyperscaler the chip team and the model team might as well be separate companies.
He puts the failure down to scale: in an organisation that large the people designing silicon and the people training frontier systems sit far enough apart that co-design never happens, so the advantage of owning both never appears. Apple is his counter-case, buying each component from whichever of thirty bidders is best, and he concedes the hypothesis is not settled.