Systems biologist after months with AI: models 'overthink locally, underthink globally' — AGI hype questioned
No-Lingonberry-5096 · reddit · 2026-09-06
A researcher who has used AI tools like Fable extensively for months in systems biology of complex diseases publishes a detailed critique of the AGI narrative. Despite being impressed by output quality, he finds fundamental limits:
- Models either nail fine detail while losing the ability to synthesize across abstraction levels (molecular kinetics, tissue dynamics, clinical chronology), or think broadly with no detail — never both, and they can't tell when or how to switch levels.
- They handle decomposable math well but can't hold and grow context in a way resembling 'thought', rearranging training data 'passably intelligently' without constructive synthesis.
- He offers four explanations: AGI talk as pre-IPO hype, leaders overestimating themselves, their intelligence being lower than assumed, or benchmarks only measuring the decomposable so the gap goes unmeasured.
His conclusion: this road doesn't visibly lead to AGI, and he hopes these companies are making other bets.
More from AGI Musings
- Senior researcher rebuts 'one-person pretraining' fear: your fundamentals matter more, not less — RexDouglass · 2026-10-23
- NBER releases 'The Economics of Transformative AI' edited by Agrawal and Brynjolfsson — JMateosGarcia · 2026-10-23
- Pedro Domingos: AI Is an Intelligence Lever — the Smarter You Are, the Smarter It Makes You — pmddomingos · 2026-10-23
- Anil Seth: Consciousness Is a Property of Life, Not Computation — Building Conscious AI Is a Bad Idea — anilkseth · 2026-10-23
- Pedro Domingos predicts 2027 will see the most security vulnerabilities fixed in history — pmddomingos · 2026-10-23
- AI+Lean theorem proving loses to Bitter Lesson: OpenAI math gains come from non-formalized reasoning — Singularitarian · 2026-10-23