AI Progress Runs at the Speed of Its Slowest Bottleneck: Compute or Deployment
menhguin · x · 2026-09-13
The author reiterates their long AI timelines view: the current progress flywheel depends on data, compute, and deployment revenue, none of which supports an RSI-speed trajectory.
- Core argument: AI progress occurs at the speed of the slowest bottleneck, currently compute or deployment, both unlikely to unblock within 2-3 years
- They also argue current architectures are too stochastic, requiring full model loops over millions to trillions of tokens, making rapid recursive self-improvement infeasible
More from AGI Musings
- 'AI bubble bursting': CEO slowdown messaging may trigger Monday crash, user warns — SumitGup · 2026-09-13
- What domain expertise still can't be trusted to Claude or ChatGPT? — sartomiki · 2026-09-13
- Circuit complexity is stuck — and AI could be the perfect adversarial partner to crack it — _onionesque · 2026-09-13
- OpenAI Researcher Warns AI-Driven Military Power Will Concentrate in Frontier Labs — jachiam0 · 2026-09-13
- SaaS CEOs about to miss a quarter suddenly discover 'we must pace the frontier' — parker_lyman · 2026-09-13
- tszzl: I hope a thousand minds can bloom — the outcome depends on how much chaos ensues — tszzl · 2026-09-13