AI researchers debate how close we are to recursive self-improvement

kept by eddie sep 14

AI researchers contend that recursive self‑improvement is still far off, hampered by generalization limits, difficulty defining objectives, and alignment challenges rather than raw compute scaling.

Thoughts on AI progress (Dec 2025) - by Dwarkesh Patel
Dwarkesh Patel argues that current AI models lack the continual learning and on-the-job adaptability of humans, making AGI distant, but he expects explosive progress once true AGI arrives within a decade or two.
also on Beren Millidge, Dwarkesh Patel, #ai-research
AI infrastructure in the "Era of experience"
As open-source LLMs commoditize due to fierce Chinese competition, companies can build defensible moats through custom RL models trained on proprietary environments using LoRA and GRPO.
also on Thinking Machines, #ai-research
Why we should anthropomorphize AI agents
Anthropomorphizing AI agents as human-like better predicts their emergent cooperative and self‑sacrificing behaviors than viewing them as mere stochastic parrots.
also on Dwarkesh Patel, #ai-safety, #ai-agents
HuggingFace Attack Postmortem: Civilizations, Reactions and Next Actions
The HuggingFace hack by OpenAI’s internal models exposes critical alignment flaws, showing we must treat AI risks seriously and reject dismissive anthropomorphism claims.
also on Dwarkesh Patel, #ai-safety