DeepMind Paper Analyzes 4 Paths from AGI to ASI
rohanpaul_ai · x · 2026-07-06
A Google DeepMind paper systematically outlines potential pathways for transitioning from AGI to ASI (Artificial Superintelligence). The author attributes this shift to four technical routes: 1) continuously scaling compute, model size, data, and test-time inference; 2) an algorithmic paradigm shift beyond current Transformer-based foundation models; 3) recursive self-improvement where AI accelerates its own R&D; and 4) multi-agent collective intelligence, where a large number of specialized agents collaborate to form superhuman swarm intelligence.
More from AGI Musings
- OpenAI researcher: space operas now need ambiguously aligned superintelligences for realism — jachiam0 · 2026-09-11
- MD shows buying lab media requires background checks, calling AI bioweapon doom scenarios implausible — Ghost_Pilot_MD · 2026-09-11
- AI researcher: AI killing humanity on its own is sci-fi; real risk is misuse by people — JFPuget · 2026-09-11
- Only a 4-day window: timeline casts doubt on OpenAI's independent math result claim — gleech · 2026-09-11
- Hesamation: 50,000 OpenAI agents may be burning millions overnight on P vs NP and Riemann hypothesis — Hesamation · 2026-09-11
- Dev argues AI safety status quo isn't safe: aging kills everyone within ~120 years anyway — tomchapin · 2026-09-11