Embodied AI2023
Genesis Authors, Genesis-Embodied-AICarnegie Mellon University, Massachusetts Institute of Technology +5
GPU-native physics engine unifying rigid-body, fluid, cloth, and deformable solvers in one Python framework for robotics and embodied-AI research. Built by a 20+ lab collaboration, now backed by Genesis AI, with generative tools to author 4D scenes.
AI Train2023
Collection of runnable model implementations — LLaMA, Mistral, Stable Diffusion, Whisper, CLIP, plus LoRA fine-tuning — ported to the MLX array framework so they run natively on Apple silicon's unified memory rather than CUDA.
AI Infra2023
Provides a NumPy-like array framework for building and training ML on Apple silicon, with Python, C/C++, and Swift APIs plus PyTorch-style higher-level modules. Features lazy evaluation, composable AD/vectorization, and a unified-memory multi-device model so arrays can be used on CPU and GPU without explicit copies.
AI Image2023
Provides a diffusion-model studio for image, video, audio-video, editing, LoRA, and full training workflows so many model families share one inference and training framework.
AI Infra2023
Provides a PyTorch-native platform for experimenting with and scaling generative AI training, including composable parallelism, checkpointing, float8, logging, and Llama recipes.
AI Audio2023
Builds real-time voice and multimodal AI agents as composable streaming pipelines. Vendor-neutral: swap among 20+ STT, 20+ LLM and 30+ TTS providers over WebRTC or WebSockets, and compose multi-agent systems with handoff and parallel workers.
AI Agent2024
Organizes reusable AI prompts as Markdown 'Patterns' you run from the CLI — summarize a video, extract claims, rate content. Switch among 20+ providers (OpenAI, Claude, Gemini, Ollama) and reach them via CLI, web UI, or REST API.
AI Infra2024
Serves large language and multimodal models with low latency and high throughput using RadixAttention, continuous batching, structured outputs, parallelism, quantization, and broad accelerator support.
AI Agent2024
Python framework for building and serving LLM agents in production: a unified event bus for real-time frontends and human-in-the-loop, fine-grained tool permissions, multi-tenant serving, and tool/code execution sandboxed via Docker or E2B.
AI Agent2024
Gives developers low-level primitives for building stateful single-agent, multi-agent, and graph-based control flows, with built-in human-in-the-loop checkpoints, persistent cross-session memory, and token-level streaming.
AI Agent2024
Controls customer-facing LLM agents turn-by-turn against deterministic guidelines instead of one big system prompt, surfacing only the rules and tools that apply each turn. Adds journeys, pre-approved canned responses, and traces for auditable behavior.
AI Image2024
Produces real-time 3D reconstructions from multi-view images using Gaussian splatting, with on-device training and interactive viewing across native desktops, Android, and the browser. Uses WebGPU and the Burn ML framework to ship dependency-free binaries, a CLI, live training visualization, and streaming .ply support.