Podcast Atlas

E162.康波周期中的AI：新技术总在萧条期爆发，bad times make good people

source Updated 2026-07-08 Tags: Podcast, Macro, Ai, Investing, Cycles

Summary

This 面基 episode uses Kondratiev Cycle thinking to connect AI, long-wave innovation, macro investing, and personal career choice. The guest argues that AI is likely the core technology of a sixth long wave, but still belongs to the broader information revolution because it processes and absorbs existing information more efficiently. The episode’s practical synthesis is that new technologies often surface in weak periods, so Depression Driven Innovation, Risk Parity, Macro Asset Expression, and preparation under bad conditions matter more than fixed-cycle prediction.

Key Claims

  • Joseph Schumpeter-style economic-cycle thinking and Technology Installation Cycle thinking should be separated: one asks why growth and downturns recur, while the other asks how new technologies move from installation to broader deployment.
  • A technology wave should be judged by whether core production technology, key production factors, infrastructure, and a techno-economic paradigm align, not by one breakthrough alone.
  • The guest’s background in the 周金涛 strategy lineage at 中信建投证券 explains why the episode treats long cycles as an investment research method rather than a mystical calendar.
  • Kondratiev Cycle analysis is useful only when it studies mechanism, reversal drivers, and nested cycles; fixed-year prophecy is treated as a misuse of the framework.
  • The current macro setting is described as closer to long-wave depression than recovery because the real economy has not yet shown a decisive broad-based improvement.
  • Depression Driven Innovation explains why weak periods can produce new companies and technologies: old technology profits decline, firms overbuild capacity, and capital searches for new profit sources.
  • AI is presented as the likely core technology of a sixth Kondratiev Cycle, while still extending the information-technology revolution that began in the 1970s.
  • In Carlota Perez terms, the episode places AI near an installation or introductory stage and leaves room for an early-bubble break before wider social and economic deployment.
  • The episode qualifies simple AI-bubble arguments: stronger AI Investment Metrics may show real demand, but AI Equity Valuation Risk remains if investors pay for the whole long wave too early.
  • Real estate cycle analysis should distinguish total population from marriage-age and homebuying-age population; the guest had previously expected a possible real-estate bottom around 2025 to 2027.
  • Gold Monetary Anchor is framed through debt, hegemonic transition, central-bank balance sheets, and monetary-system change, not only through a 1970s inflation comparison.
  • Sell-side macro research rewards clear narratives, while buy-side investing has to translate probabilities into positions, sizing, and risk budgets.
  • Risk Parity is presented as a way to earn from broad credit and money expansion across stocks, bonds, commodities, and other assets, but it can suffer when liquidity crises make correlations rise together.
  • The episode’s structure-focused macro view treats inflation, wages, debt, and distribution as jointly driven by deeper factors rather than one variable mechanically causing another.
  • Geopolitical Cycle Macro matters because the world is moving away from a stable unipolar environment; non-steady macro analysis should handle changing boundaries and constraints.
  • Macro Asset Expression is the practical test of a macro story: translate views into equity style, bond duration, commodity exposure, sectors, and risk controls instead of stopping at narration.
  • The guest expects China’s private-fund industry to move from single-asset stock-long products toward multi-asset strategies as alpha becomes harder to earn and property absorbs less liquidity.
  • The closing theme, “bad times make good people,” argues that bad environments do not remove opportunity; they raise the preparation threshold for people who want to catch the next cycle.

Key Quotes

“bad times make good people” — the episode’s closing frame for preparation under poor macro conditions.

“新技术总在萧条期爆发” — title-level claim connecting weak periods with technological renewal.

“周期研究不能机械套年份” — methodological caution against treating long cycles as a fixed timetable.

Connections

Contradictions