DataTalks podcasts: why good models fail in production, and calibrating biased LLM judges
Al_Grigor · x · 2026-10-12
Two DataTalksClub podcast episodes this week:
- Today: Why do good models fail in production? Miguel Otero Pedrido, who went from quantum field theory to fashion recommender engines and insurance agentic workflows, argues a good model isn't enough — you must build the whole system around it, covering engineering practices that take AI projects from concept to production.
- Tomorrow: Can you trust your evals? IBM AI engineer Tejas Kumar covers LLM-judge biases (length, position), calibrating AI judges against human labels, using deterministic checks instead of expensive model evals, and evaluating RAG systems stage by stage.
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