AI wasn’t overhyped. Almost everyone underestimated it.

kept by eddie oct 26

AI progress has consistently outpaced forecasts from superforecasters, experts, and the public, while AI leaders' predictions proved more accurate.

How far behind are open models? — LessWrong
Open models lag behind closed frontier models by 8–10 months on private benchmarks and 4–6 months on public, with the gap growing since DeepSeek R1.
also on FrontierMath, METR, #benchmarks, #ai-research, #ai
AI IQ — Intelligently Measuring AI Intelligence
The piece presents a methodology that maps public benchmark scores to IQ estimates across seven dimensions, enabling comparison of AI models by intelligence, speed, and cost.
also on FrontierMath, #benchmarks, OpenAI, Anthropic
Alex Imas and Phil Trammell – What remains scarce after AGI?
Economists argue that after AGI, scarcity may shift to human-relational services, but the labor share's fate depends on whether new capital varieties prevent satiation.
also on Epoch, #ai
Life At The Edge - Asad Khaliq
Computing advances in fractals of concentration and diffusion; AI inference is now diffusing to edge devices, but cloud models remain essential for peak capability.
also on Epoch, #ai
Can AI self-improvement overcome diminishing returns?
Despite rapid AI progress, the self‑improvement feedback loop is too weak to overcome diminishing returns, making a rapid intelligence explosion unlikely without a major breakthrough.
also on #forecasting, METR, #ai-research, OpenAI, Anthropic, #ai