Billionaire Investor Just Revealed the AI Bet That Could Pay Off Big in 5 Years

Zerodha co-founder Nikhil Kamath and Coinbase CEO Brian Armstrong warned that the sky-high valuations of premium AI companies like OpenAI and Anthropic face a massive structural threat.

The alarm arrives amid growing investor skepticism, as both leaders compared today’s AI frenzy to the dot-com crash and past crypto bubbles.

A billionaire investor says if you bet against every AI company today, you’d be rich in five years, and the CEO of Coinbase [Brian Armstrong] quietly agrees it might be a bubble.[Nikhil] “If I were to take every private company in AI and short their stock today, in five years,… pic.twitter.com/pXglaN9u7a

— BILLIONAIRE UNIVERSITY® (@TheBillionaireU) July 17, 2026

Why Kamath Would Short Every AI Company Today

Speaking on the “People by WTF” podcast, both leaders drew direct parallels between the current AI boom, the 2000s dot-com collapse, and standard crypto market bubbles.

Their shared concern centers on expensive proprietary models losing ground to cheaper alternatives.

Kamath framed the risk in personal, investor terms. He said shorting every private AI company today could, in five years, make him money, comparing the moment to the Internet bubble.

“Like me, the stock trader investor, I’m starting to feel at this point that if I were to take every private company in AI and short their stock today, in five years, I might make money… It feels a bit like… the ‘Internet bubble’,” Kamath said.

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Six bubbles.Five crashes.One crash left.1972 → Nifty Fifty Bubble → Crashed1989 → Japanese Bubble → Crashed1999 → Dot-Com Bubble → Crashed2007 → Housing Bubble → Crashed2016 → Chinese Bubble → Crashed2026 → AI Bubble → Cra…Every cycle looked different.… https://t.co/Q9yBUxUt7k pic.twitter.com/V0cIYMx4aC

— Wimar.X (@DefiWimar) June 23, 2026

The Zerodha co-founder also expects the industry to fragment. A market dominated by a few American giants would give way to a regional, self-reliant economy built through reverse-engineering and rapid local development.

Under that view, individual nations stop importing expensive models and build their own. India would run its own domestic copy, with the tokens and energy sitting locally, functional enough for everyday use even if not cutting-edge.

“If the world goes in that direction, I don’t see the reason to pay the multiples that these private companies have today,” Zerodha co-founder argued.

🇨🇳 China just torched the U.S. AI lead in a single afternoon.Moonshot AI, a little-known Beijing startup, dropped Kimi K3 on Thursday and it instantly kicked into the top tier of global models.It beat Anthropic's Fable 5 and OpenAI's GPT-5.6 Sol on coding tests, then edged… pic.twitter.com/KGf8zdLb3V

— Mario Nawfal (@MarioNawfal) July 17, 2026

What is the 99% Cheaper Threat Armstrong Describes

Armstrong, notably, agreed with that market assessment. He pointed to a stark cost gap between elite frontier labs and the open-source models trailing right behind them.

Top-tier labs spend billions building the next breakthrough. Open-source alternatives, roughly six months behind, reach the market at a tiny fraction of that price.

The Coinbase CEO put a figure on it. Open-source models run about six months behind and cost up to 99% less for inference, so a larger share of workloads could shift toward them.

The future is open source. We need to embrace it and get on with it. Imagine if America closed the door on open source.We would explicitly be forcing American companies to pay $26-56 per 1MM tokens for the same intelligence their adversaries/competitors around the world would… https://t.co/AkIWsb2X3C

— Chamath Palihapitiya (@chamath) July 18, 2026

He drew a clear line between two futures. Elite frontier models stay valuable for highly specialized tasks like discovering new physics, but average consumers and businesses turn intensely price-sensitive.

“It makes me a little nervous when I see these valuations growing this fast as well. Like I’ve seen things like this happen before in crypto. They correct, and then there’s real value under it, so then they grow later,” Armstrong noted.

Once standard models run cheaply on everyday commodity hardware, the corporate defenses protecting high-value AI companies could dissolve entirely. That erosion sits at the heart of the warning.

Armstrong closed on a cautious note. Fast-growing valuations make him nervous, echoing patterns he witnessed in crypto, where prices corrected before real value emerged and growth resumed later.

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