Bank of England flags risk of 'sudden correction' in tech stocks inflated by AI

Access and article context

• Commenters share archive links and note this is routine HN culture to bypass paywalls.
• One reader cites the Bank of England’s own report, pointing out the “sudden correction” language applies to risky assets generally, with AI/tech singled out as particularly stretched and index‑concentrated.

AGI prospects, determinism, and limits of intelligence

• Long subthread debates whether human intelligence is deterministic and therefore reproducible in software, or whether quantum randomness and chaos matter.
• Some argue AGI is inevitable over very long timescales; others say resource and civilizational limits may stop us first.
• Another camp doubts there is any “magic level” of intelligence that can, by itself, cure cancer or invent warp drives; intelligence is constrained by data, experiments, and physics.
• Counterarguments: humans underuse available data; better algorithms and more compute could unlock cures like cancer even without radically new data.

Is there an AI bubble? Valuation, returns, and risk

• Many see AI equity valuations as obviously risky: enormous capex, modest or circular revenues, and high dependence on future demand for chips and datacenters.
• Nvidia’s and other “Magnificent Seven” valuations are cited as systemically important; an AI-led correction could hit broad indices.
• Others push back that “the market disagrees” and that claiming overvaluation without taking a financial position is cheap talk.
• Several note it’s easy to identify bubbles, hard to time the pop; most stick to diversified index investing rather than shorting.

Monetization, productivity, and use cases

• Skeptics: current LLMs can’t reliably automate even customer support; hallucinations and low willingness to pay limit upside.
• Supporters: existing models could, with more engineering, handle much support and creative work (ads, animation, illustration, media); entertainment and ad markets alone are worth trillions.
• Some heavy users report modest personal productivity gains (≈1.05x, not 10x), and question where the alleged macro productivity boost is.
• Open‑source models (Llama, DeepSeek, Mistral, etc.) are being evaluated in-house; for many use cases, small local models are “good enough,” eroding proprietary moats.

Labor, capitalism, and social consequences

• Discussion of capital’s drive to “zero labor cost” and fears that AGI would fuse capital and labor, sidelining humans from production and demand.
• Commenters worry about mass unemployment undermining political stability, yet note investors seem focused only on short‑term competitive pressure.

Macroeconomic backdrop and debt

• Thread veers into US sovereign debt, inflation, and Modern Monetary Theory:
  • One side sees debt and likely monetization as the real systemic risk, with AI as a “hail mary” for growth.
  • Others argue a sovereign issuer can’t run out of its own currency, and that “debt” is just private savings, though critics cite historical currency collapses and loss of creditor confidence.