A local inference engine for Apple silicon, built around the model.
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Sorry for the pretentious name, I know, I know.. It just contains all the pieces I would like to see a AGI model to have, and I can't stand the temptation. Before throwing rocks at me, please take a glance at the Readme, and I hope it will cover your mood a little bit. So, first of all it does work
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Your Cheat Sheet For AI Engineering Interviews at Top AI Companies - Questions and Answers.
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Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results
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Trending model on Hugging Face — text-generation, llama.cpp; 1624 likes, 2,227,879 downloads.
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Hi HN! My wife and I got deep into our family genealogy and wanted to map out all our relatives - but keep the data on our own Macs instead of uploading it to a genealogy service. Nothing we found did that, so we built Swarm, a native macOS app in Swift. It's built on GEDCOM 5.5.
hey hn, i made bailout for a pretty specific problem. you boot a fresh vm and want an agent to help get it set up, except you dont have your agent set up yet. no gh, no config, no api key handy. might not even have codex / claude code / opencode curled and loaded. or you already
I built Laya MPS, a PyTorch runtime for running Jev-style typed decisions locally on Apple Silicon GitHub repo: https://github.com/afshinm/laya-mps On an M5 Pro: - Default mode: ~32 ms latency, ~2.1 GB peak process RAM - Lowest-memory mode: ~171 ms latency, ~0.74 GB peak process