903: LLM Benchmarks Are Lying to You (And What to Do Instead), with Sinan Ozdemir
Super Data Science: ML & AI Podcast with Jon Krohn
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Evaluating AI Benchmarking and Model Performance
This chapter explores the critical challenges and methodologies in benchmarking AI models, particularly large language models. It emphasizes the necessity of a decontamination phase for training data, the significance of task-specific test sets, and the evaluation of model outputs against human judgments. The discussion also covers the complexities of multimodal models and the ongoing need for updated evaluation criteria in the face of evolving AI capabilities.
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