A full-stack LLM development toolkit from NVIDIA covering synthetic data generation, multi-backend inference, model training, and 11-category benchmark evaluation, scaling from single GPU to tens-of-thousands-GPU Slurm clusters.
An open-source framework for building, evaluating, and training general multi-agent systems. Features natural language agent creation, distributed reinforcement learning training pipeline, and complex environment interactions. Ranks top on authoritative benchmarks including GAIA, OSWorld, and VisualWebArena.
A production-ready implementation of InvisPose that enables real-time, camera-free full-body tracking through walls using commodity WiFi mesh routers and CSI signals, with advanced analytics like fall detection and multi-person tracking.
An LLM post-training framework for RL scaling by Tsinghua THUDM, deeply integrating Megatron-LM training with SGLang inference engine for distributed reinforcement learning on large models like GLM, Qwen, DeepSeek, and Llama.
An open-source framework by Stream for building vision AI agents that work with any model or video provider, leveraging Stream's edge network for ultra-low latency video experiences.
A high-throughput, low-latency inference framework designed for serving generative AI and reasoning models in multi-node distributed environments.
AI-Compass is a comprehensive open-source project that provides learning paths and practical guidelines for AI technologies, helping users from beginners to professionals build a complete AI knowledge system from fundamental theory to cutting-edge applications.
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