An embarrassment of AI

Your Radar Trends preview for February.

Mike Loukides has been keeping tabs on the tech industry, and he's finding AI everywhere. We've extracted some highlights. Who's more comfortable with AI, artists or scientists? Anthropic's survey of professionals revealed some counterintuitive findings about AI adoption in the workplace. Researchers have found that tuning a model too finely can lead to misalignment—and worse. Newsroom scamps at the Wall Street Journal tricked their AI-powered vending machine into giving away its entire stock and then convinced it to order some unusual snacks. In non-AI news, California residents can now direct the government to relay their request to delete personal data to up to 500 brokers. We hope that idea spreads. Enjoy these and other observations in this month's Radar Trends.   IN COLLABORATION WITH OUR SPONSORS Download  ›   Download ›   Download  ›   Download ›   Download  ›   Download  ›   Download ›   Download ›   Download  ›   Download ›   Interested in sponsoring an O'Reilly title? Contact sponsorships@oreilly.com.   Free live event: Liz Rice and Andy Martin on Container Security Author Liz Rice and security expert Andy Martin get together to discuss practical container security strategies, new threats and tools, and the evolving landscape of cloud native application protection. You'll have the opportunity to ask your own questions, deepen your practical knowledge of securing containers in real-world scenarios, and take away actionable insights. O'Reilly members can sign up here. If you aren't a member, register below for free.   Sign up now › Book: Architecture as Code Acclaimed software architects Neal Ford and Mark Richards present a practical framework for treating architecture like source code—using fitness functions and automated feedback to define structure, constraints, governance, security, and communication across the entire organization. With this approach, teams can continuously validate alignment with technical and business goals, reduce risk, and evolve systems with confidence.   Dive in › Audiobook: Software Engineering for Data Scientists The ability to write reproducible, robust, scalable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.   Listen now › Want your own copy of this newsletter? Sign up here. This message was sent to alexvarboffin.abbb@blogger.com. You are receiving this because you've signed up to receive email from us. Privacy Policy | Unsubscribe from All | Unsubscribe from Radar Trends O'Reilly Media, Inc., 141 Stony Circle, Suite 195, Santa Rosa, CA, 95401 (707) 827-7000