Discover the Best AI Resources
Curated essentials, no noise — just what matters
A vision-language-action foundation model and reference stack for generalized humanoid and cross-embodiment robot manipulation. Provides pretrained checkpoints, demo datasets, and tooling for fine-tuning, evaluation, and deployment (ONNX/TensorRT); released as Early Access.
Provider-agnostic framework for orchestrating multi-agent LLM workflows in Python: agents that delegate via handoffs, function/MCP/hosted tools, input/output guardrails, automatic session memory, and a visual tracing UI for debugging runs.
Runs and fine-tunes LLMs locally on Apple silicon via the MLX framework, pulling thousands of Hugging Face models with one command. Adds 4- and 8-bit quantization, LoRA and full fine-tuning, prompt caching, and distributed inference across Macs.
Trains multi-step LLM agents with reinforcement learning (GRPO) on your own tasks, wrapping existing agent code behind an OpenAI-compatible client. Its RULER mode scores trajectories with an LLM judge, so there's no reward function to hand-write.
Provides 7×24 automated customer service for the Xianyu marketplace with multi-expert routing, context-aware dialogue, and a laddered bargaining system. Built in Python and designed to run against an LLM provider with browser-cookie integration for web interactions.
Benchmark for evaluating OCR systems that convert PDFs and scans into Markdown and structured text: 1,403 PDFs and 7,010 unit tests covering text presence/absence, reading order, tables, and math formula accuracy. Diverse sources and ODC-BY-1.0 license for research use.
Transforms unstructured financial content—papers, news, blogs, and filings—into a queryable semantic knowledge graph for retrieval-augmented research. Combines domain-tuned LLMs, embedding-based search, and modular ingestion pipelines; aimed at quant research teams and institutional workflows.
Connects AI coding agents (Cursor, Claude Code) to Figma through a WebSocket bridge, letting an agent read a design and edit it programmatically. Includes a Figma plugin and 40+ MCP tools for text, styling, components, and bulk edits.
Splits LLM inference into separate prefill and decode GPU pools, then routes requests with KV-cache awareness to cut redundant recomputation. Reports up to 30x throughput on DeepSeek-R1 (GB200 NVL72) and works across TensorRT-LLM, vLLM, and SGLang.
Bridges LLM-driven AI assistants to the Unity Editor so models can create scenes, edit C# scripts, manage assets, run tests and automate game-dev workflows. Exposes 47 focused MCP tool entrypoints, supports many MCP clients, and is MIT-licensed for local use.
Autonomously executes diverse biomedical research tasks by combining LLM reasoning, retrieval-augmented planning, and code-based execution. Includes a web UI and Gradio demo, a curated Know‑How library, MCP integration, and a biology-tailored reasoning model (Biomni‑R0).
Real-time DETR detector on a DINOv2 backbone, covering detection, segmentation, and keypoints. Ships in six sizes (Nano to 2XL), beats YOLO on the COCO speed-accuracy curve, and transfers better to non-COCO real-world domains.