What Actually Matters in AI: Not ARR or Benchmarks, But Frontier Models, RSI and China
Afinetheorem · x · 2026-10-15
A widely-shared X post lists what does and doesn't matter in AI: ARR, revenue, benchmarks and non-frontier labs' "caught up" releases don't; recursive self-improvement, internal frontier model capabilities, AI-made novel discoveries, safety advances, low-latency LLM-driven robots and computer use, and China do.
More from AGI Musings
- What My Math Teacher Taught Me About Doing Math with AI, via Terence Tao's Math 2.0 — Stefania_druga · 2026-10-15
- Most Software Has No Access Layer Between the Agent and the App — That's the Problem — usehive · 2026-10-15
- Musk Endorses Prediction: Soon the Whole World Will Run on Code Nobody Has Read — elonmusk · 2026-10-15
- Researchers warn AI-generated faulty health 'causal inferences' are worse than math slop — ivan_bezdomny · 2026-10-15
- Asymco: AI Chose Taxi Driving Over Trucking, Where 10% of Jobs Go Unfilled — asymco · 2026-10-15
- Noam Brown: 10k-agent swarms scale near-linearly but coordinate worse than 10k humans — gabriberton · 2026-10-15