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:

http://ibm.biz/developer-security-conference