Staving off disaster through AI safety research
While covering Applied Machine Learning Days in Switzerland, Chris met El Mahdi El Mhamdi by chance, and was fascinated with his work doing AI safety research at EPFL. El Mahdi agreed to come on the show to share his research into the vulnerabilities in machine learning that bad actors can take advantage of. We cover everything from poisoned data sets and hacked machines to AI-generated propaganda and fake news, so grab your James Bond 007 kit from Q Branch, and join us for this important conversation on the dark side of artificial intelligence. Sponsors: Linode – Our cloud server of choice. Deploy a fast, efficient, native SSD cloud server for only $5/month. Get 4 months free using the code changelog2018. Start your server - head to linode.com/changelog Rollbar – We move fast and fix things because of Rollbar. Resolve errors in minutes. Deploy with confidence. Learn more at rollbar.com/changelog. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com. Featuring: El Mahdi El Mhamdi – Website, X Chris Benson – Website, GitHub, LinkedIn, X Show Notes: El Mahdi El Mhamdi on LinkedIn Google Scholar Personal blog World Health Organization | Ten threats to global health in 2019 AggregaThor The Hidden Vulnerability of Distributed Learning in Byzantium Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent Asynchronous Byzantine Machine Learning (the case of SGD) Upcoming Events: Register for upcoming webinars here!