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Beat Buesser | Origin Story | Adversarial Robustness Toolbox
IBM Developer Podcast
English - July 22, 2020 20:17 - 29 minutes - 23.3 MB - ★★★★ - 5 ratingsTechnology Business enterprise technology hybrid cloud cognitive applications artificial intelligence iot main frame watson ibm Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: Andrea Crawford & Mike Spisak | DevOps & Security | IBM Garage Method
Next Episode: OpenEEW & Grillo founder Andy Meira
Join us for a conversation with researcher, machine learning engineer, and software developer, Beat Buesser. His current work focuses on automated machine learning, data science, computer vision, adversarial machine learning, and security in artificial intelligence. Beat tells us his origin story, as well as, about his work on the Adversarial Robustness Toolbox (ART) which is a Python library for defending, certifying, and verifying ML models against the adversarial threats of evasion, poisoning, extraction and inference.
ART: https://github.com/IBM/adversarial-robustness-toolbox
IBM Research profile: http://ibm.biz/beat-buesser
You can watch the replay of Beat's talk from the IBM Cloud Native Digital Developer Conference here: