task horizons

Peter Wildeford 🇺🇸🚀✓ @peterwildeford Deep learning is hitting a wall [Chart: METR "Task duration (for humans) where logistic regression of our data predicts the AI has a 50% chance of succeeding," y-axis 0 to 7 hours, x-axis 2023-2025, points for GPT-4 near 0 rising through o3, GPT-5, Claude Opus 4.5 (~5.3 hrs), GPT-5.2 (high) (~6.5 hrs), exponential dashed trend line; juxtaposed with an illustration of a brick wall on the right, ironically undercutting the "hitting a wall" caption.] 5:28 AM · Feb 10, 2026 · 170.4K Views

Noam Brown @polynoamial · 11h When GPT-5 was released, some folks claimed AI progress was hitting a wall, whereas others said progress would continue. GPT-5.2 was released 2 months ago. GPT-5.3-Codex was released 2 days ago and is twice as token efficient for coding. It's clear who turned out to be correct. [Chart: METR "Time-horizon of software engineering tasks different LLMs can complete 50% of the time" — y-axis task duration in hours humans need, x-axis LLM release date 2020-2025. Points trace exponential growth from GPT-2/GPT-3 near 0 through GPT-3.5, GPT-4, o3, GPT-5, Claude Opus 4.5, up to GPT-5.2 (high) at ~7 hours by 2025/2026.] 💬 76 🔁 122 ♥ 1.2K 📊 106K Taelin @VictorTaelin · 6h do you expect this trend to keep going? at this pace we'd reach unthinkably absurd values at the end of this year? 💬 8 🔁 1 ♥ 147 📊 7.2K Noam Brown @polynoamial · 6h Yes. I think by the end of the year the main challenge for @METR_Evals will be measuring horizons that long.