Thinking Machines on the Limits of AI
alex_verem · x · 2026-07-15
This post summarizes and comments on an essay by Thinking Machines Labs, arguing that: AI and the "local knowledge" in an economy cannot be fully absorbed by a single, centralized model.
Drawing on Hayek's critique of central planning, the author emphasizes that the knowledge underpinning the economy is often tacit, localized, and constantly updated—like a chef tweaking a recipe, a shop owner adjusting prices, or a company's internal decision rules. Feeding all this into a giant model doesn't eliminate this decentralization.
The post extends this logic to AI's impact on jobs:
- AI excels at tasks like chess or math where the board is fully visible and the goal is static.
- Real-world jobs rarely look like this; critical knowledge often lives in human judgment and collaboration rather than documentation.
- Therefore, AI is best suited for structured, clearly bounded tasks, not roles relying on tacit knowledge and constantly shifting environments.
Related event: Thinking Machines Explores AI Limits via Hayek(3 posts)→
More from AGI Musings
- After Microsoft's 60K layoffs, pundit predicts 50-60% headcount cuts at big companies — krishnan · 2026-10-27
- 'Explain how AI isn't impacting productivity': 27% workforce cut sparks debate — alvelda · 2026-10-27
- David Patterson: by 2035, superintelligence brings 100x incomes and post-scarcity housing — davidpattersonx · 2026-10-27
- Claude now handles 27% of Anthropic's R&D, up from zero months ago — thursdai_pod · 2026-10-27
- Resy's scorched-earth war on booking agents sets up a clash with big platforms — matt_slotnick · 2026-10-27
- Michael Levin on AI Emails: Read the Papers First, Then Write Me — drmichaellevin · 2026-10-27