Episode summary
He Predicted the AI Bubble in 2023 | Doug Clinton and Gene Munster on Why We're Still in 1996
Excess Returns
· · 53 min · Guests: Gene Munster, Doug Clinton
Summary
Doug Clinton argues AI is still early in its bubble cycle, comparing the market to 1995 or 1996 rather than 1998. He says the trade likely has a few years left because the real bottlenecks are building and powering data centers, while demand for intelligence keeps accelerating. Gene Munster agrees that the infrastructure buildout looks underappreciated, especially energy, and both guests frame AI as a conversion of electricity into intelligence.
They spend much of the conversation on frontier model competition and enterprise adoption. The guests say Claude Code and OpenAI’s Codex have made AI useful for real coding and productivity work, and that enterprise spending is surging as companies burn through inference budgets faster than expected. They also argue that model quality is still improving quickly, with the leaders changing by task: GPT is their top overall model, Claude is strong for ideation, and DeepSeek has performed best in their earnings-direction tests.
On investing, they expect more disruption for knowledge workers over the next five years, but also new jobs for people who become “detectives” and bring missing data into enterprises. They see the AI capex boom continuing, think hyperscaler spending will stay stronger than Wall Street expects, and view energy, nuclear, storage, space infrastructure, and orbital data centers as important second-order themes.
Key takeaways
- Doug Clinton still thinks AI is earlier than the market assumes and says the trade is closer to 1995 or 1996 than 1998.
- The guests say enterprise adoption is surging, with Claude Code and Codex turning AI into a practical coding and productivity tool.
- Gene Munster expects more acute knowledge-worker unemployment over the next five years, but says people will adapt by learning how to use AI.
- The guests see power, nuclear, storage, and data-center infrastructure as the key bottlenecks in the AI buildout.
- In Intelligent Alpha’s testing of about 700 stocks, GPT ranks best for earnings-direction prediction, while DeepSeek has been strongest on the pure stock-picking portfolio.
- They expect AI IPOs and major capital spending to reshape market indexes and create source-of-funds pressure for mega caps.
Notable quotes
“we're converting electricity into intelligence right now like that's exactly what's happening”
“I think it might actually still be closer to 1995, 1996. I think there's probably still more room to go on the AI trade”
“we are absolutely in the days of utility now”
“I think AI for any individual, it can either supercharge you or it can make you irrelevant”
How the episode opens
What AI really means just as a first principle is we're converting electricity into intelligence right now like that's exactly what's happening and so if that's true and the demand for intelligence is seemingly infinite I think the demand for power is seemingly infinite that's a very basic question that investors should ask themselves do you believe the management in these companies is competent at seeing the future and if the answer is yes then uh they should be rewarded for making these investments. And if the answer is no, then they should be uh penalized for that. I do believe we're going to see in the near term, we'll call it a five years, more acute knowledge worker unemployment than we saw around mobile or the internet.
And uh but I ultimately I think it does fix itself uh because people realize you got to get on board. We test about 700 different uh stocks across all these models and I'll give you the drum roll to see any guesses on on who's the top model right now before I re reveal it. Doug Jean, thank you guys very much for coming back on excess returns.
You are in high demand these days. So, and
The fact that we can get you for, you know, 45 or 60 minutes is we really appreciate it and our audience does too cuz you guys always have a lot of uh great things to say when it comes to technology and I always appreciate your ability to you know explain these things in a way that our audience I think can get you know a lot from these. It's not you guys can go in depth when you need to but at the same time you can kind of talk talk high level.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai adoption
- frontier model race
- ai infrastructure and energy demand
- market bubble dynamics
- investing in the ai stack
Companies and tickers mentioned
- GOOGL
- GOOG
- AAPL
- OpenAI
- Anthropic
- SpaceX
- Apple
- Intelligent Alpha
- Deepwater Asset Management
- DeepSeek
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Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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