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Practical AI: Machine Learning, Data Science, LLM
The path towards trustworthy AI
Oct 29, 2024
Elham Tabassi, Chief AI Advisor at NIST, Avthar Suothin from Timescale, and David Hsu, CEO of Retool, dive into the essential topic of trustworthy AI. They discuss NIST's AI Risk Management Framework and its pivotal role in ensuring safe AI development, particularly in sensitive areas like healthcare. The conversation highlights privacy concerns in data management and the importance of transparent frameworks. They also explore the evolution of AI risk management and the significance of community feedback in shaping effective guidelines.
51:46
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Quick takeaways
- NIST emphasizes the importance of collaborating with diverse stakeholders to develop guidelines that enhance the trustworthiness, reliability, and fairness of AI systems.
- The AI Risk Management Framework (AI RMF) provides organizations with a structured approach to identify, measure, and manage AI risks effectively over time.
Deep dives
Introduction to Timescale and Postgres for AI
Timescale is a company focused on enhancing the capabilities of Postgres, particularly in handling time series data and AI applications. Developers can leverage existing knowledge of Postgres to create AI applications without needing to learn completely new technologies. Using tools such as the PGAI project, developers can seamlessly integrate AI functionalities like retrieval-augmented generation and search into their projects. This approach not only simplifies the learning curve but also enables developers to take on new and exciting roles as AI engineers utilizing familiar technologies.
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Listen to the best highlights from the podcasts you love and dive into the full episode