Reading up on Epoch AI

AI inference market will grow to ~$350B by 2027, surpassing the $161B database market and fundamentally reshaping software unit economics.

Epoch AI reports that the cost to achieve a given level of AI performance has fallen roughly 47% per quarter since 2023, outpacing historic tech price drops.

Anthropic unveils three metrics—AI-led R&D share (26%), agent oversight coverage (100%), and safety compute share (6%)—to increase transparency in frontier AI development.

Code was a medium for thought, not just output; AI agents risk eroding intuition and alignment unless new tools let us think in more human ways.

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.

Epoch AI estimates frontier labs use less than half of global AI compute, but OpenAI and Anthropic may soon dominate, requiring economic transformation to sustain scaling.

Epoch AI analyzes job postings from OpenAI, Anthropic, xAI, and DeepMind to reveal shifting strategies toward go-to-market roles, hardware bets like robotics and devices, and differing approaches to compute and data sourcing.

Expert AGI timelines contracted then expanded in 2025 as reasoning model gains proved costly to scale, though steady progress and growing revenue undercut radical pessimism.

Frontier AI labs are automating research to create vast AI workforces that self-improve, radically accelerating capability growth by 2026.

Global AI computing capacity from chips has grown 3.3x per year since 2022, doubling every seven months, with NVIDIA supplying over 60%.

Benchmark scores are dominated by a single 'general capability' dimension, with the second component mainly identifying a 'Claudiness' factor.