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The Decoder

The AI industry's platform trap is starting to look a lot like Microsoft's OpenAI buys Ona to push Codex toward long-running, autonomous coding tasks Jeff Bezos' AI startup Prometheus closes $12 billion round at a $41 billion valuation Free Deezer tool lets users on any streaming service check their playlists for AI music OpenAI vs. Anthropic: A price war over API tokens is brewing Dario Amodei's new essay reads like a Cold War playbook for the AI age Claude Fable 5: Anthropic admits "wrong tradeoff" after invisibly throttling rival AI researchers Google's new open model DiffusionGemma generates text from noise instead of word by word OpenAI's IPO slips as Altman tells staff to expect a public offering "within the next year" Anthropic study shows AI needs hours, not weeks, to build exploits from security patches OpenAI wants its biggest data center yet, and Nvidia would back the bill Claude Fable 5: The first Mythos model is powerful, expensive, and heavily filtered Germany's National Security Council greenights an AI Safety Institute modeled after the UK's AISI Google's NotebookLM now runs its own cloud computer with code execution and agent-based research Anthropic releases Claude Fable 5 and Mythos 5 with major gains in coding and science Google's Gemini 3.5 Live Translate delivers real-time voice translation across 70+ languages SpaceX wants to put data centers in orbit, and Musk says it's no big deal Landmark German ruling declares Google's AI Overviews are Google's own words and makes it liable for false answers Beijing's $295 billion AI buildout would require 80 percent domestic chips, locking out US suppliers Apple Intelligence gets a second shot with help from Google and Nvidia OpenAI now says "entirely automating everything is not the future we want" OpenAI says going public is "a complicated set of tradeoffs" and is unsure about the timing Microsoft Research's Lens proves detailed captions matter more than raw scale for training efficient image generators Intel gets a second life as Google and Nvidia explore it as a TSMC backup for AI chips Most companies are flying blind on AI spending Frontier Radar #3: How agentic AI is turning tokens into a business metric Instagram AI chatbot breach may have affected over to 20,000 accounts, Meta discloses Microsoft tightens rules for conflict zones after investigation into Israel's military use of Azure Moonshot AI targets a $30 billion valuation, more than six times its late-2025 worth Deepseek topped Ramp's trending software vendors in June 2026 as US companies chase cheaper AI
NYU finance professor Damodaran warns an AI crash could h...
Matthias Bastian · 2026-06-20 · via The Decoder

Aswath Damodaran, a finance professor at New York University, warns that a potential crash in the AI sector could be more painful than the bursting of the dot-com bubble around 2000.

In the podcast "Intangible Economy," he explains that unlike the dot-com era, the AI industry needs massive investments in physical infrastructure and much of it is financed with debt. If a correction hits, the damage wouldn't just fall on shareholders but could ripple out across society.

Damodaran also questions whether the AI business model can scale the way people expect. In his view, AI isn't a traditional software business. Costs don't automatically drop toward zero as more users come on board. Every additional use burns compute, similar to how Spotify pays for each stream.

That makes economies of scale far weaker than in Netflix's case, which Damodaran contrasts with Spotify: Netflix's high content costs get spread across a growing subscriber base, while Spotify pays per stream. Growth paired with thin margins could actually destroy value. Moreover, there's the risk of price erosion from Chinese competitors like Deepseek. Margins are already low.

Damodaran also warns about the bull case, because the business model would then be about replacing entire jobs, not selling AI as a tool. If AI actually delivers on this promise, "half of white-collar workers" would lose their jobs.

"The scary thing is the big stories you tell that can justify AI, if they come true, are going to create some insane costs for society that we better start thinking about right now," Damodaran says. He calls this scenario the "AI fever dream."

Big tech is entering unfamiliar territory

Damodaran says that he owns five of the seven so-called "Magnificent Seven" stocks, including Amazon, which he's held on and off since 1997. He says he has to accept that these companies are changing at a fundamental level because of their heavy AI investments. Instead of just tracking margins and new business lines, he now also has to analyze capital expenditures and depreciation.

For companies that used to be capital-light, that never mattered. These companies grew with minimal capital spending. Now they're building massive factories and infrastructure that will be depreciated over ten years but could be obsolete after five. "I'm not sure they really know what they're getting themselves into," Damodaran says.

Apple's cautious approach looks smarter to him. Many analysts have criticized Apple for not jumping in headfirst, but Damodaran sees it as a strength because "we undervalue restraint in business." Apple can sit back, watch others make mistakes, and learn from them instead of pouring billions into areas where it has no experience, Damodaran says.

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