Bristech MLOps: Dan Jeffries - AI Red Teaming (Sept 2020) скачать в хорошем качестве

Bristech MLOps: Dan Jeffries - AI Red Teaming (Sept 2020)

When AI goes wrong and how to fix it fast - Dan Jeffries, CTE, Pachyderm Video Chapters (please click on Chapter Heading to start playing from that time) 0:00 Introduction by Nic Hemley 0:38 Talk by Dan Jeffries 29:00 Q+A chaired by Nic Hemley With algorithms making more and more decisions in our lives, from who gets a job, to who gets hired and fired, and even who goes to jail, it’s more critical than ever to get our intelligent systems talking to us so people can step in when things go wrong. In the coming decade, organizations will face incredible pressure from regulators and the general public and that means every team needs a plan in place to find and fix mistakes fast or risk PR nightmares and financial disasters. Through this talk I’ll show you how to build an AI Red Team to deal with everything from edge cases to outright AI breakdowns, while getting you ready to embrace the latest breakthroughs in explainable AI tomorrow. About Daniel Daniel is Chief Technology Evangelist at Pachyderm. He’s also an author, engineer, futurist, pro blogger and he’s given talks all over the world on AI and cryptographic platforms. He’s spent more than two decades in IT as a consultant and at open source pioneer Red Hat. With more than 50k followers on Medium, his articles have held the number one writer’s spot on Medium for Artificial Intelligence, Bitcoin, Cryptocurrency and Economics more than 25 times. His breakout AI tutorial series “Learning AI If You Suck at Math” along with his explosive pieces on cryptocurrency, “Why Everyone Missed the Most Important Invention of the Last 500 Years” and “Why Everyone Missed the Most Mind-Blowing Feature of Cryptocurrency,” are shared hundreds of times daily all over social media and been read by more than 5 million people worldwide. Recent Talks include: Red Hat Open Shift Commons keynote 2b Ahead Think Tank in Berlin Twitter: @Dan_Jeffries1 Read Dan’s articles on Medium.