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Study uncovers lost 'golden age' of languages
A pharmacy chain in Vermont implemented AI for efficiency
Show HN: RunNburn – Run a 295B Moe from a 98GB GGUF on a 64GB RAM Desktop
runNburn is an Apache-2.0 Rust inference engine for quantized GGUF models that are too big for your fast memory. The core idea: weights stay file-backed (mmap), host residency stays under an explicit byte budget (--ram-budget), and GPU caches are sized from detected free/total VRAM — never from device-name presets. There is no conversion step, no sidecar cache files, no silent requantization. The GGUF on disk is the single source of truth. The result that made me want to post this: Tencent's Hy3
Flume Water Monitor 915 MHz Security Is Pretty Good
Overengineered Calculator: Zig and QBE
Manual: •.,:;?·
Logic for Programmers by Hillel Wayne
Show HN: Full stack development from one codebase web, Android, and iOS
There's never been a better time to commit financial fraud
Show HN: A local merge queue for parallel Claude Code agents
I have been pushing up to 90 commits a day on a MacBook Air via 4-5 parallel agents. As you can imagine when all the agents try to build, test and run dev servers on an 8GB machine it is the fast lane to a force quit and restart. I also did not want to pay the CI minutes on 90 pushes a day. So I designed a local merge queue to have all commits land one at a time and fully tested. Hopefully this helps other folks with more modest machines. Appreciate any feedback.