✨ The Age of AI is starting to bloom
Deep Dives
Explore related topics with these Wikipedia articles, rewritten for enjoyable reading:
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Dot-com bubble
15 min read
The article directly addresses whether AI represents a speculative bubble, making the dot-com bubble the most relevant historical parallel. Understanding how that bubble formed, inflated, and burst provides essential context for evaluating current AI investment patterns and the author's argument that 'classic conditions for a bubble simply are not present.'
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Prediction market
15 min read
The author cites Kalshi, Metaculus, and Manifold Markets predictions as evidence for his AGI timeline views. Understanding how prediction markets aggregate information, their track record on technological forecasts, and their theoretical basis would help readers critically evaluate whether these probability estimates should be trusted.
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Productivity paradox
15 min read
The article's central question—whether AI advances are 'spreading throughout the US economy' productively—directly echoes the famous Solow productivity paradox ('You can see the computer age everywhere but in the productivity statistics'). This historical phenomenon of technology investments failing to show up in productivity metrics is essential context for evaluating AI's economic impact.
My fellow pro-growth/progress/abundance Up Wingers in America and around the world:
Two of the questions I’m most frequently asked by reporters or podcast hosts: “What is your AGI or superintelligence timeline?” and “Are we in an AI bubble?”
Which is fine. When I’m the interviewer, I often ask the same things. They’re important questions, after all — with big implications. Let me briefly offer what are probably contrarian answers:
First, “superintelligence super soon” isn’t my baseline. That’s an opinion based partly on a) my natural caution from having experienced more than a few tech hype cycles, b) my conversations with tech folks, and c) predictions markets. On that final point:
Kalshi: “When will OpenAI achieve AGI?” — 41 percent (before 2030)
Metaculus: “Date of ‘weakly’ general AI” — Nov. 20, 2027
Metaculus: “Date of ‘general’ AI” - July 2033
Manifold Markets: “When will AGI arrive?” - 2034
Manifold Markets: “By 2028, will AI produce a clearly noticeable shift in U.S. GDP, GDP per capita, unemployment, or productivity trends?” - 30 percent
All that said, if in 10 years AI has evolved to something we can generally agree is AGI or beyond, that hardly seems like a distant date to me.
Bursting bubble speculation
Second, we’re not in an AI bubble as of right now. Annual AI investment has risen by roughly $200–300 billion since 2023. Which is a lot, definitely. Yet Goldman Sachs in estimates that generative AI could create about $20 trillion in present-discounted economic value for the US, including around $8 trillion in capital income for firms. Their earlier work implies roughly a 15 percent eventual boost in US labor productivity from generative AI—equivalent to roughly $4–5 trillion at today’s output—and micro-studies often find task-level productivity gains on the order of 25–30 percent. This is hardly the stuff of crazy-got-nuts speculative froth.
Nor is the AI infrastructure build-out obviously running ahead of reality. Goldman also estimates that demand for AI training queries is growing at roughly 350 percent a year and demand for frontier models at about 125 percent, while compute efficiency improves by only about 40 percent annually. Finally, the Financial Times’s Richard Waters keenly notes that the much-touted $1.4 trillion data-center pipeline has only about 10 percent actually committed. The world faces a shortage of capacity, not a glut. Meanwhile, the giants funding the boom mint
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