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A Decade of AI Safety and Trust // Petar Tsankov // MLOps Podcast #218

Mar 12, 2024
58:04
Snipd AI
The podcast delves into AI safety and trust over the past decade, emphasizing the importance of reliability and transparency in deploying models. It explores the contrasting educational environments in the US and Switzerland, highlighting the journey of the speaker. Discussions cover challenges in ensuring trust in AI models, the impact of generative AI, and the need for comprehensive testing post-deployment to build trust.
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Podcast summary created with Snipd AI

Quick takeaways

  • Decoupling models from data is crucial for AI trust.
  • Office location impacts tech collaboration and growth.

Deep dives

Deep Dive into AI Trust and Robustness

The podcast delves into the importance of ensuring AI trust, where AI research, traditionally focused on optimizing accuracy, now faces challenges in production due to various factors. Models not being decoupled from data is emphasized, highlighting the significance of upstream data quality. Lattice flow's focus on detecting model blind spots to enhance system robustness is discussed.

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