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Databricks Chief AI Scientist Jonathan Frankle joins Radical Partner Vin Sachidananda for a special conversation from Radical Ventures’ AI Masterclass Series. Together, they explore what it takes to move AI from academic insight to real-world, enterprise-scale deployment. Drawing on Jonathan’s experience co-founding Mosaic ML and now leading research at Databricks, the discussion covers why early efficiency gains feel “quaint,” how open-source serves as scientific proof, and why evaluation remains the missing infrastructure for enterprise AI adoption. A practical conversation for founders and technical leaders building AI systems that need to perform in production.
By Radical VenturesDatabricks Chief AI Scientist Jonathan Frankle joins Radical Partner Vin Sachidananda for a special conversation from Radical Ventures’ AI Masterclass Series. Together, they explore what it takes to move AI from academic insight to real-world, enterprise-scale deployment. Drawing on Jonathan’s experience co-founding Mosaic ML and now leading research at Databricks, the discussion covers why early efficiency gains feel “quaint,” how open-source serves as scientific proof, and why evaluation remains the missing infrastructure for enterprise AI adoption. A practical conversation for founders and technical leaders building AI systems that need to perform in production.

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