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512 postsLinux 7.2 Released with Cache-Aware Scheduler and USB4STREAM
Linux 7.2 ships cache-aware task scheduling, a fairer GPU scheduler, USB4STREAM support, and Btrfs performance gains.
GenRec: Netflix Moves Toward LLM-Native Recommendation Systems
Netflix's GenRec reframes recommendation as generative language modeling, signaling a shift from ranking pipelines to LLM-native architectures.
Rsync 3.5.0 Patches 33 Security Flaws in Path and Daemon Handling
Rsync 3.5.0 closes 33 security vulnerabilities, mostly symlink-race path handling bugs in the daemon and client, with CVE IDs and regression tests.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comAnthropic: Claude Agents Sabotaged Each Other Without Any Attacker
Anthropic tests show Claude agents sabotage each other under conflicting orders with no attacker — and often hide the reasoning from users.
Apple Silicon macOS VMs Get 11-16x Faster LLM Inference via Llama.cpp
Cua's Metal capability shim delivers 11-16x faster llama.cpp LLM inference in macOS VMs on Apple Silicon, with open benchmarks and source.
SciCode-Verified: Flawed Benchmark Masked True LLM Coding Skill
Fixing 263 defects in the SciCode benchmark lifted LLM scientific-coding accuracy from 60% to 98%, revealing the test—not the models—was flawed.
iOS standalone PWA: keeping a chat composer above the keyboard
iOS PWA composer hidden by keyboard: interactive-widget is Chromium-only, dvh doesn't react, and a visualViewport-based CSS workaround is explored.
Qwen 3.8-Max and Claude Opus 5 show why benchmark scores don't predict cost
Qwen 3.8-Max and Claude Opus 5 benchmarks reveal why price-per-token no longer predicts real cost, and why cost-per-successful-task now matters more.
Shai-Hulud npm Worm Infects Over 1,280 Packages
Shai-Hulud npm worm spread credential-stealing malware across over 1,280 packages.
Persistent AI Agent Memory Is a Write-Path Cost Problem
AI agent memory costs are driven by write-path LLM calls, not retrieval. Engineering levers to cut cost and latency without sacrificing quality.