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Waymo Reveals Remote Workers In Philippines Sometimes Advise Its Driverless Cars
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Good News: We Saved the Bees. Bad News: We Saved the Wrong Ones.
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Bitcoin Dropped Nearly 30% This Week. But Why?
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Firefox Announces 'AI Controls' To Block Its Upcoming AI Features
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Apple Plans to Allow Outside Voice-Controlled AI Chatbots in CarPlay
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Free Bi-Directional EV Chargers Tested to Improve Massachusetts Power Grid
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Moltbook, Reddit, and The Great AI-Bot Uprising That Wasn't
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Claude Code is the Inflection Point
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New Bill in New York Would Require Disclaimers on AI-Generated News Content
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Neocities Founder Stuck in Chatbot Hell After Bing Blocked 1.5 Million Sites
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Waymo is Having a Hard Time Stopping For School Buses
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Hollywood's AI Bet Isn't Paying Off
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Amazon's Tax Bill Plunges 87% After Tax Cuts
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An in-kernel machine-learning library
What is the goal of using ML models in Linux kernel? The main goal is to employ ML models for elaboration of a logic of particular Linux kernel subsystem based on processing data or/and an efficient subsystem configuration based on internal state of subsystem. As a result, it needs: (1) collect data for training, (2) execute ML model training phase, (3) test trained ML model, (4) use ML model for executing the inference phase. The ML model inference can be used for recommendation of Linux kernel subsystem configuration or/and for injecting a synthesized subsystem logic into kernel space (for example, eBPF logic).
It is rigorously undocumented and there are no real users, so it's not entirely clear what the purpose is, but there are undoubtedly interesting things that could be done with it.
Memory Prices Have Nearly Doubled Since Last Quarter
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Salesforce Shelves Heroku
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Hidden Cameras in Chinese Hotels Are Livestreaming Guests To Thousands of Telegram Subscribers
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AI.com Sells for $70 Million, the Highest Price Ever Disclosed for a Domain Name
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Big Tech's $1.1 Trillion Cloud Computing Backlog
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