paul marshall

Marshall Wace's internal token usage tracks OpenRouter/Anthropic growth curves; recursive self-improvement (agents improving agents overnight) will shift AI from human-prompted to autonomous 24/7 operation, driving massive compute demand.

Paul Marshall contends AI is eroding traditional information advantages held by institutions, enabling retail investors to access comparable knowledge and thus increase their share of trading activity, making markets more competitive while questioning whether this enhances overall market efficiency.

AI commoditizes nowcasting (data assembly/earnings anticipation) but humans still excel at synthesizing fundamentals, technicals, and market ecology (leverage, risk-manager behavior, buyer/seller dynamics) to spot distress opportunities.

Paul Marshall argues AI represents an intelligence explosion comparable to the Cambrian biological revolution or steam engine, with token usage exploding and recursive self-improvement imminent, signaling early-stage transformative potential despite corporate adoption delays.

US semi-index and Korean market trade at 5-10 year and all-time low valuations respectively; shares have only risen in line with earnings, suggesting the AI hardware cycle has further to run before bubble territory.

Current market lacks three bubble ingredients: rates aren't low enough to fuel speculation, valuations aren't extended (semis at decade lows), and Korean ETF leverage has already corrected from $60B to $20B. Bubble will come later.

Paul Marshall identifies three conditions for a genuine AI bubble: sustained low interest rates encouraging speculation, significantly extended asset valuations, and unsustainable leverage levels, noting current valuations and leverage (e.g., Korean ETF example) do not yet meet bubble thresholds.

Near-term AI capex drives chip and energy inflation; 6-24 months out, productivity gains will weaken entry-level labor markets, lowering rate pressure and creating a bullish macro backdrop for equities.