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3 articles tagged Model Evaluation.
Elise AI's Head of Applied Research discusses the engineering challenges of deploying AI in housing and healthcare. The analysis covers the necessity of hybrid model architectures, the critical role of rigorous evaluation systems, and the strategic shift from lab research to high-stakes real-world impact.
An executive analysis of METR's time horizon metrics, the impact of Opus 4.5 on developer productivity, and the strategic implications of compute constraints on AI capability growth. This brief covers independent threat modeling, the shift to agentic coding, and the limitations of current benchmarking methodologies.
OpenAI Frontier Evals leaders explain why SWE-bench Verified is saturated and contaminated, driving the industry toward SWE-bench Pro. The discussion covers benchmark evolution, contamination detection, and the need for harder, real-world coding evaluations.
