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The Intangible Economy with Kai Wu: Daily Summaries Delivered
by Excess Returns
The Intangible Economy with Kai Wu explores the hidden forces reshaping the modern economy and their implications for investors. AI and the broader technology revolution are changing how we live, work, and create value. In each episode, Kai sits down with investors, researchers, and other experts to discuss how innovation and other intangible forces - such as brands, human capital, and network effects - are transforming markets and investment outcomes.
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- 3 weeks ago1h 16m
What Past Capital Cycles Can Teach Us About AI with Edward Chancellor
Edward Chancellor joins Kai Wu to discuss what financial history and capital cycle theory can teach investors about today’s AI boom. They explore why transformative technologies can still produce terrible investor returns, how overinvestment develops, where anti-bubbles may be forming, and what past episodes like the railway mania, the dot-com bubble, China’s investment boom and the post-2008 interest rate regime suggest about the risks and opportunities today.Guest links:Edward Chancellorhttps://www.edwardchancellor.com/Papers and articles discussed:Valuing AI: Extreme Bubble, New Golden Era, or Bothhttps://www.gmo.com/americas/research-library/valuing-ai-extreme-bubble-new-golden-era-or-both_viewpoints/Markets have poor scorecard for spotting AI losershttps://www.reuters.com/commentary/breakingviews/markets-have-poor-scorecard-spotting-ai-losers-2026-04-24/There’s no such thing as a good bubblehttps://www.reuters.com/commentary/breakingviews/theres-no-such-thing-good-bubble-2025-10-09/Big Booze can sweat off its multi-year hangoverhttps://www.reuters.com/commentary/breakingviews/big-booze-can-sweat-off-its-multi-year-hangover-2025-07-10/Topics covered:How capital cycle theory applies to the AI data center boomWhy railway mania, autos, aircraft and the dot-com bubble offer lessons for todayWhy markets often fund major technology transitions but fail to identify the winnersThe prisoner’s dilemma driving hyperscaler AI spendingWhether AI demand can justify the supply being builtHow GPU depreciation and AI capital spending may affect reported earningsWhy hallucinations and reliability may limit the total addressable market for large language modelsThe case for looking at AI anti-bubbles instead of shorting the bubble directlyWhy China shows that strong GDP growth does not guarantee strong shareholder returnsHow intangible capital, SaaS valuations and human capital fit into capital cycle analysisWhether bubbles can be good for society while still being bad for investorsWhy the long-term interest rate cycle may have changedThe role of gold in a world of expensive stocks, rising debt and vulnerable bondsTimestamps:00:00 Edward Chancellor on capital cycles, bubbles and AI04:42 Why the railway mania became a classic overinvestment cycle09:00 Why markets fund technology booms but often miss the winners13:19 The prisoner’s dilemma behind AI spending17:30 Will AI demand justify the supply being built20:00 How capital spending can inflate profits before the bust25:08 The AI Hindenburg moment and the limits of large language models30:55 Why AI hype may exceed the proven technology35:55 Why the anti-bubble may matter more than shorting AI40:00 The energy transition bubble and the opportunity in overlooked assets45:08 China’s lesson on GDP growth and shareholder returns49:27 Big Booze, GLP-1s and the Lindy effect54:23 Can intangible capital have its own capital cycle59:54 SaaS valuations and the index creation warning signal01:04:10 Why bubbles can help society but hurt investors01:09:09 Why long-term rates may be in a new multi-decade cycle01:14:07 Why Edward Chancellor still sees a role for gold
- Mar 31, 20261h 1m
Michael Mauboussin: Base Rates, AI Adoption, and Investing in the Intangible Economy
This episode of The Intangible Economy explores how AI, intangible assets, and unprecedented capital investment are reshaping the future of markets. Michael Mauboussin joins Kai Wu to break down why today’s AI expectations may be historically unmatched—and what that means for investors trying to assess risk, returns, and who ultimately captures value.The conversation moves from base rates and AI growth expectations to competitive dynamics, capital cycles, and the fundamental shift toward intangible-driven business models that are changing how we think about valuation, moats, and market structure.Papers and Resources Discussed:Bayes and Base Rates: How History Can Guide Our Assessment of the Futurehttps://www.morganstanley.com/im/en-us/institutional-investor/insights/consilient-observer/bayes-and-base-rates.htmlThe Impact of Intangibles on Base Rates – https://www.morganstanley.com/im/publication/insights/articles/article_theimpactofintangiblesonbaserates.pdfMeasuring the Moat: Assessing the Magnitude and Sustainability of Value Creation – https://www.morganstanley.com/im/publication/insights/articles/article_measuringthemoat.pdfOne Job: Expectations and the Role of Intangible Investments – https://www.morganstanley.com/im/publication/insights/articles/article_onejob.pdfCapitalism Without Capital: The Rise of the Intangible Economy – https://books.google.com/books/about/Capitalism_without_Capital.html?id=J3SYDwAAQBAJA Better Estimate of Internally Generated Intangible Capital – https://pubsonline.informs.org/doi/10.1287/mnsc.2022.01703Underestimating the Red Queen: Measuring Growth and Maintenance Investments – https://www.morganstanley.com/im/publication/insights/articles/article_underestimatingtheredqueen.pdfExplaining the Recent Failure of Value Investing – https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3442539Guest Links:Michael Mauboussin TwitterTopics Covered:-Why OpenAI’s projected growth would be unprecedented in market history- How base rates provide a reality check on AI expectations- The role of diffusion models and adoption curves in forecasting technology- Why massive capital investment in AI may follow past boom-bust cycles- Lessons from large-scale infrastructure projects and why timelines break- How intangible assets change the distribution of business outcomes- The rise of “fat tails” and why more companies now massively win or fail- Who captures value in AI across the stack from chips to applications- Why competition may drive AI profits toward consumers, not producers- How accounting distorts intangible investment and misleads investorsTimestamps:00:00 Intro and OpenAI growth expectations vs historical base rates04:32 Why no company has ever achieved 100%+ sustained growth at scale08:47 Lessons from megaprojects and AI infrastructure buildouts13:18 Intangible assets and why outcomes now have fatter tails18:36 Why big tech is growing faster than historical precedents23:52 Where value accrues in AI and why consumers may benefit most28:21 Barriers to entry in AI including capital, talent, and scale32:47 The risk of overinvestment and historical parallels to past bubbles37:26 Game theory and competitive signaling in AI capital spending41:58 Why investment returns—not “asset light” narratives—drive value46:12 How accounting fails to capture intangible investment properly50:44 Breaking down SG&A into maintenance vs investment spending55:03 Why understanding reinvestment and ROI is the core investing skill59:18 Final thoughts on uncertainty, expectations, and base rates in AI
About The Intangible Economy with Kai Wu
The Intangible Economy with Kai Wu explores the hidden forces reshaping the modern economy and their implications for investors. AI and the broader technology revolution are changing how we live, work, and create value. In each episode, Kai sits down with investors, researchers, and other experts to discuss how innovation and other intangible forces - such as brands, human capital, and network effects - are transforming markets and investment outcomes.
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