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  • St. Vincent - St. Vincent - Broken Man (Jimmy Kimmel Live / 2024) - YouTube

    “Broken Man” live on Jimmy Kimmel From the new album - All Born Screaming – out now. Listen: https://STV.lnk.to/allbornscreamingID See St. Vincent live: https://STV.lnk.to/Tour FOLLOW ST. VINCENT: https://ilovestvincent.com/ https://www.instagram.com/st_vincent https://www.tiktok.com/@stvincentofficial https://twitter.com/st_vincent https://www.facebook.com/St.Vincent Lyrics: on the street

      St. Vincent - St. Vincent - Broken Man (Jimmy Kimmel Live / 2024) - YouTube
    • React 19 lets you write impossible components | Mux

      React 19 is here. And with it? Complex and flexible new features. Incredible optimizations. And a whole new way of thinking about your app. But when building a marketing site, are React 19’s features over-engineered? Or is it all worth the effort? For the last 18 months, these features have slowly been rolling out in React Canary and the Next.js App Router. And, for the last 18 months, we’ve been

        React 19 lets you write impossible components | Mux
      • How ransomware abuses BitLocker

        Introduction Attackers always find creative ways to bypass defensive features and accomplish their goals. This can be done with packers, crypters, and code obfuscation. However, one of the best ways of evading detection, as well as maximizing compatibility, is to use the operating system’s own features. In the context of ransomware threats, one notable example is leveraging exported functions pres

          How ransomware abuses BitLocker
        • Mapping the Mind of a Large Language Model

          Today we report a significant advance in understanding the inner workings of AI models. We have identified how millions of concepts are represented inside Claude Sonnet, one of our deployed large language models. This is the first ever detailed look inside a modern, production-grade large language model. This interpretability discovery could, in future, help us make AI models safer. We mostly trea

            Mapping the Mind of a Large Language Model
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