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Fast and Accurate Code Search for Agents. Uses ~98% fewer tokens than grep+read
A kernel library written in tilelang
Apple Silicon (MLX) port of Karpathy's autoresearch — autonomous AI research loops on Mac, no PyTorch required.
AI agents running research on single-GPU nanochat training automatically
SwiftUI presentation software, every slide is a URL
Open-source CUDA, Triton and HIP compiler targeting multiple GPU and CPU architectures.
A community trust management system based on explicit vouches to participate.
⚡ A fast Git hook manager written in Rust, designed as a drop-in alternative to pre-commit, reimagined.
My learning notes for ML SYS.
Run OpenClaw, (formerly Moltbot, formerly Clawdbot) on Cloudflare Workers
Bf-Tree is a modern read-write-optimized concurrent larger-than-memory range index in Rust from MS Research.
A curated list of papers and resources based on the survey "Agentic Reasoning for Large Language Models"
Sutskever 30 implementations inspired by https://papercode.vercel.app/ | For Agents, use https://github.com/pageman/Sutskever-Agent | Polyglot / Multi-Backed version at https://github.com/pageman/s…
Model Context Protocol Servers
Post-training with Tinker
A minimal yet professional single agent demo project that showcases the core execution pipeline and production-grade features of agents.
A template for deploying a Talos Kubernetes cluster including Flux for GitOps
flash attention tutorial written in python, triton, cuda, cutlass
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
TabICLv2: A state-of-the-art tabular foundation model
All Algorithms implemented in Python
Sysinternals jcd (jump change directory) is a Rust-based command-line tool that provides enhanced directory navigation with substring matching and smart selection. It's like the cd command, but wit…
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)