
Special: Defeating AI Defenses (with Nicholas Carlini and Nathan Labenz)
Future of Life Institute Podcast
Navigating Openness and Security in Machine Learning
This chapter discusses the implications of transparency in machine learning and its effect on organizational practices regarding proprietary methods. It contrasts the openness in cryptography with AI, emphasizing that a lack of disclosure may undermine the security and reliability of algorithms.
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