Equation 11 · The Hardest Unsolved Problems in AI Agent Evaluation and Reliability
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Read the formula alongside the article passage below. Each part has a deeper page with its role in the equation, the supporting passage and nearby citations.
This mathematical expression combines the displayed quantities; its precise role follows from the surrounding article text. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.
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Symbol T_50
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subscript
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The clearest empirical trend in this area comes from METR, which measured how the length of software tasks that leading agents can complete at even odds has changed over time, expressed as a time horizon - the length of task, in expert-human time, that an agent completes successfully half the time. Kwa and colleagues report that this time horizon has been doubling roughly every seven months since 2019, which can be written as an empirical fit
Sources cited in the article section
- [5] Underspecification Presents Challenges for Credibility in Modern Machine Learning ↗
- [1] AI Agents That Matter ↗
- [6] WebArena: A Realistic Web Environment for Building Autonomous Agents ↗
- [4] Measuring AI Ability to Complete Long Software Tasks ↗
These citations give research context. Read each source to check which claims it supports.
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