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How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


How Microsoft Scales Testing and Safety for Generative AI with Sarah Bird - #691

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
57 minutes
Released:
Jul 1, 2024
Format:
Podcast episode

Description

Today, we're joined by Sarah Bird, chief product officer of responsible AI at Microsoft. We discuss the testing and evaluation techniques Microsoft applies to ensure safe deployment and use of generative AI, large language models, and image generation. In our conversation, we explore the unique risks and challenges presented by generative AI, the balance between fairness and security concerns, the application of adaptive and layered defense strategies for rapid response to unforeseen AI behaviors, the importance of automated AI safety testing and evaluation alongside human judgment, and the implementation of red teaming and governance. Sarah also shares learnings from Microsoft's ‘Tay’ and ‘Bing Chat’ incidents along with her thoughts on the rapidly evolving GenAI landscape.

The complete show notes for this episode can be found at https://twimlai.com/go/691.
Released:
Jul 1, 2024
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.