Pod Insights Finshots Daily Why Michael Burry is going short on AI About this episode In today’s episode on 28th November 2025, we explain why the famous short seller is going short on AI when everyone is going bullish on AI stocks.
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Transcript 0:00 Speaker 00 Hello folks, you're tuned into Finshots Daily. In today's episode, we explain why the famous short seller is going short on AI when everyone is going bullish on AI stocks.
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0:59 Speaker 00 Almost three weeks ago, Michael Burry, the short seller who bet against the housing market before the 2008 crisis, closed down his asset management company, Scion Asset Management. He deregistered the hedge fund on November 10th, 2025, which officially meant he'd be stepping away from professional money management. When the company was closed, the news couldn't help but speculate if the Scion of the Scion was actually going to retire, which is why he came out clean stating that he's clearly not going to. That led to the next guessing game. Why did he step away and what comes next? It started with the new rules by Securities and Exchange Commissions, that is SEC, or that's the American version of SEBI.
1:41 Speaker 00 A tougher regulatory climate for registered investment advisors between 2023 and 25. Things like mandatory quarterly fee reports, audited statements, a heavier paper trail of positions and high transparency, combined with the fact that Michael Burry's name packs a punch, meant he couldn't do what hedge funds existed to do in the first place. Take quiet asymmetric unlikely bets without giving out your position. Now for a short seller, that's someone who bets a stock will fall and tries to profit when its price drops. That can mean everything. Each time his firm would file a disclosure, the media would make their own interpretations, which trickle down to smaller retail traders who like to copy trade bigger players. That can move a stock irrationally.
2:26 Speaker 00 It made it impossible to operate the way he had all these years and with that, he closed down the fund and started a new venture. A newsletter, that's right. A few weeks into closing down his firm, Pari started his own newsletter, aptly called Cassandra Unchained. After his newfound freedom from regulatory filings, he started posting on Substack and X with the same warning. The AI boom is looking more and more like a bubble in the making, similar to the dot com crash of the early 2000s. His thesis is simple. The companies paving the path to AI, chipmakers, cloud giants, AI computing companies and of course, the infrastructure builders are investing heavily to build the future. And because the hardware and software are so unique, they are also extremely expensive.
3:11 Speaker 00 Think billion dollar data centers, massive computing clusters and GPUs whose long term return on investment is still uncertain at the scale. He's even given this a name. Supply side gluttony. Enormous spending chasing unproven economics. He argues that many AI heavy firms are assuming their expensive GPUs and servers will last five to six years and are depreciating this hardware over that timeframe, when in reality, it may become outdated much sooner. And if he's right, these firms are overstating their profits by as much as one seventy six billion dollars between 2026 and 2028. But why does this matter? To answer that, let's understand some basic depreciation.
3:52 Speaker 00 Say you run a cap company and your fleet consists of cars that cost 10 lakh rupees a unit. With the heavy use in the city, the car might be good for five years of use before its maintenance costs more than it brings in and also before customers start complaining about it. By that logic, your depreciation cost should be about 2 lakh rupees a year. But on paper, you suddenly claim the cars will last 10 years. Now you only show 1 lakh rupees as the annual depreciation. Depreciation cost. The annual cost drops to one lakh rupees and profits look much healthier. Even though nothing has changed in cash terms, it all works fine until year five arrives and the car is actually at the end of its life.
4:30 Speaker 00 But your books pretend it has another five years left. But when the cards come crumbling down, the company has to take a huge hit to its balance sheet just to clean up this accounting. This is what Michael Burry was getting at when some tech companies suddenly double the useful life of their assets for depreciation, hence the one seventy six billion dollar figure. Sure, you could argue that today's GPUs are built better, but the pace of AI progress is even faster, which means the hardware powering it can become obsolete much sooner than companies assume. From the outside, it might look like Michael Burry is shorting AI itself because the companies are so large, but he's really betting against the pricing of the technology behind it.
5:13 Speaker 00 And history shows that big tech shifts don't always reward investors equally. The dot com era still has survivors, but most never delivered the returns investors had hoped for. Similarly, the rate at which current AI companies are building aggressively makes it look unlikely that investors will see returns or earnings to match. And even if they are to match it, earnings will have to grow at exponential rates in the coming years, while their customers have yet to show any sign of durable profits that will sustain such growth. This fault line is what he's targeting. Now, keeping that in mind, we also have the depreciation accounting factor.
5:49 Speaker 00 Meaning, many AI companies are stretching the useful life that GPUs and servers save from three years to six years, so that annual depreciation expense becomes smaller today. But if revenue drops in the future and investors start questioning these assumptions, companies may be forced to reset the useful life to something more realistic. When that happens, they must catch up on all that depreciation they delayed. That's the much higher depreciation cost all at once or a double hit that could shattered today's belief in endless exponential profits. This is why Burry's positioning makes sense to him. Shorting the stocks, in his view, puts him in the right place when stretching. valuations finally collide with more realistic cash flows. But does this mean Bari is questionably right, you ask?
6:34 Speaker 00 Well, not everyone agrees. Nvidia for one pushed back strongly after Bari's comments gained traction. The company argued that GPUs and AI servers remain useful for years and simply get shifted to less demanding tasks as they age. Analysts like Bernstein also say that the debate hasn't settled yet and that the real useful life could be longer, shorter, or simply too early to model with confidence. Yet, Bari isn't waiting for consensus. To him, the best asymmetric opportunities appear before the numbers settle. So realistically, one of two things might happen. AI monetization and capital expenditure ramp up fast enough to justify today's prices, giving bullish investors the win. Or the pricing is too far ahead of fundamentals and Bari's contrarian bet pays off.
7:19 Speaker 00 Until then, the market will keep leaning one way and Bari will keep leaning the other, making it a long story, making it a long shot that only time can settle. A fun fact before we end the story. In Greek mythology, Cassandra was a priestess who could foresee disasters but was cursed so that no one believed her. After shutting down his asset management company and freeing himself from disclosure rules, Michael Bari named his newsletter Cassandra Unchained, as we mentioned, which is a nod to both the myth and Warren Buffett's idea of Cassandra syndrome, where market warnings are dismissed until it's too late. All right, folks, I'll see you tomorrow. Until then, have a fantastic Friday. Thank you for listening to today's episode. And if you want to share your feedback or suggestions,
8:04 Speaker 00 do drop us an email to [email protected] . Until next time.
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