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In this episode of AI + a16z, Distributional cofounder and CEO Scott Clark, and a16z partner Matt Bornstein, explore why building trust in AI systems matters more than just optimizing performance metrics. From understanding the hidden complexities of generative AI behavior to addressing the challenges of reliability and consistency, they discuss how to confidently deploy AI in production.
Why is trust becoming a critical factor in enterprise AI adoption? How do traditional performance metrics fail to capture crucial behavioral nuances in generative AI systems? Scott and Matt dive into these questions, examining non-deterministic outcomes, shifting model behaviors, and the growing importance of robust testing frameworks.
Among other topics, they cover:
Follow everyone:
Scott Clark
Distributional
Matt Bornstein
Derrick Harris
Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.
4.6
2626 ratings
In this episode of AI + a16z, Distributional cofounder and CEO Scott Clark, and a16z partner Matt Bornstein, explore why building trust in AI systems matters more than just optimizing performance metrics. From understanding the hidden complexities of generative AI behavior to addressing the challenges of reliability and consistency, they discuss how to confidently deploy AI in production.
Why is trust becoming a critical factor in enterprise AI adoption? How do traditional performance metrics fail to capture crucial behavioral nuances in generative AI systems? Scott and Matt dive into these questions, examining non-deterministic outcomes, shifting model behaviors, and the growing importance of robust testing frameworks.
Among other topics, they cover:
Follow everyone:
Scott Clark
Distributional
Matt Bornstein
Derrick Harris
Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts.
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