
Adversarial Examples Are Not Bugs, They Are Features with Aleksander Madry - #369
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Unveiling Adversarial Examples
This chapter explores the emergence and significance of adversarial examples in machine learning, challenging the notion that they are merely glitches. The speakers discuss the inherent features of these examples, emphasizing the discrepancies between human expectations and the models' pattern recognition processes. Through personal narratives and technical insights, they highlight the implications for model robustness, explainability, and the ongoing complexities in understanding machine learning systems.
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