Capabilities · Concept
Rated Conceptual Arguments Dataset for Hard AI/Philosophy Questions
951 expert-rated critiques of 442 position texts for evaluating LLM argument quality on conceptual AI safety and philosophy questions.
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Both advance evaluation of AI systems on open-ended scientific/conceptual quality rather than solely verifiable answers.
+4 growthExpert-rated conceptual argument data can ground scalable evaluation of contested AI governance and safety claims.
+3 growthSignal sources
Signal sources
Dated facts from primary sources in this direction.
The length of software tasks AI agents can do autonomously at 50% reliability has doubled about every 7 months — and since 2024 closer to every ~3 months.
METR →In one year scores rose by 18.8, 48.9 and 67.3 points on MMMU, GPQA and SWE-bench; real-world software solve rate jumped from 4.4% to 71.7%.
Stanford HAI — AI Index 2025 →On SWE-bench Verified (500 real GitHub issues), autonomous coding agents reached ~80–86% by late 2025, up from under 50% in early 2025.
Epoch AI →