Remember the good ole days when we spent youthful hours playing hide and seek with our friends in the park? Well it turns out that game of hide and seek isn’t just for humans anymore. Researchers have begun putting A.I. to the test by having it play this favorite childhood game over and over and having the software optimize its strategies through automated reinforcement training.  In today’s episode, hosts Nic Fillingham and Natalia Godyla speak with Christian Seifert and Joshua Neil about their blog post Gamifying machine learning for stronger security and AI models, and how Microsoft is releasing this new open-sourced code to help it learn and grow.  In This Episode, You Will Learn:What is Microsoft’s CyberBattleSim? What reinforcement learning is and how it is used in training A.I. How the OpenAI Gym allowed for AI to be trained and rewarded for learning  Some Questions We Ask:Is an A.I. threat actor science fiction or an incoming reality? What are the next steps in training the A.I.? Who was the CyberBattleSim created for? Resources:OpenAI Plays Hide and Seek…and Breaks The Game! 🤖 Gamifying Machine Learning for Stronger Security and AI Models Christian Seifert’s LinkedInJoshua Neil’s LinkedInMicrosoft Security BlogNic’s LinkedInNatalia’s LinkedInRelated:Listen to: Afternoon Cyber Tea with Ann JohnsonListen to: Security Unlocked: CISO Series with Bret Arsenault Discover and follow other Microsoft podcasts at microsoft.com/podcastsSecurity Unlocked is produced by Microsoft and distributed as part of The CyberWire Network.  Hosted on Acast. See acast.com/privacy for more information.

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