Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides multi-task long-speech evaluation data for eight speech-understanding tasks (ASR, summarization, QA, translation, emotion, speaker counting, content separation, language detection). Includes 101,822 long audio files and ~204,881 annotated examples with JSONL task splits for easy loading.
Runs a local-first, full AI stack—LLM inference, chat UI, voice, agents, workflows, RAG, and image generation—deployable with one command. Auto-detects hardware and bootstraps a small model for instant chat while larger models download; supports Linux, Windows, macOS and optional cloud/hybrid modes.
A fast, local document parser that extracts spatial text with bounding boxes from PDFs and other formats. Bundles Tesseract OCR and supports HTTP OCR servers, multi-language bindings (Rust, Node, Python, WASM) and screenshot generation; best for lightweight local pipelines but less suited to very complex or heavily scanned documents.
Provides a local MCP server that returns precise, symbol-level code (functions, classes, imports) via tree-sitter parsing so AI agents send only the bytes they need—commonly cutting code-reading token usage 95%+ and enabling compact packed responses for further savings.
A challenge repository for training the best language model that fits inside a 16,000,000‑byte (16MB) submission artifact; provides baseline training code, FineWeb bpb evaluation, a public leaderboard, and compute-grant instructions for short 8×H100 runs.
Turns a PC, Mac, or Linux machine into a private AI server with one-command installers: local LLM inference, a ChatGPT-style web UI, voice, agents, RAG, workflows, image generation, hardware-aware model selection, and optional cloud/hybrid modes.
Autonomous white-box AI pentester for web apps and APIs. It reads your source code, maps the running app, then runs specialized agents that fire real proof-of-concept exploits for injection, XSS, SSRF, and auth flaws — reporting only what it can exploit.
Filtered subset of the OPUS 4.6 parallel corpus that isolates reasoning-related translation examples and removes 979 refusals, providing a cleaner 3,000×-filtered dataset for training or evaluating NLP models focused on reasoning in translation.
Runs a persistent, self-modifying AI agent locally with durable identity, memory, and versioned history across tasks. Provides native desktop and headless CLI runtimes, coordinated subagent swarms, configurable remote or local GGUF models, and reviewed self-evolution via Git.
Turns authorized ad-account exports or reads into dated, source-grounded audits, channel and budget plans, creative briefs, experiments, monitoring, and versioned JSON reports. Read-only by default; supports twelve ad platforms and drafts safe account changes behind capability, verification, and rollback gates.
Cleaned reasoning dataset of problem→thinking→solution triplets derived from Opus 4.6, provided in Parquet with ~2,160 cleaned rows (original 3,305). Filters remove empty/short/refusal/non‑substantive responses; hosted on Hugging Face under Apache‑2.0.
Desktop AI agent that automates tasks against your real working environment—local files, terminals, browser workflows, slides/docs, data analysis and scheduled jobs. It pairs a local app layer (sessions, permissions, SQLite persistence) with the OpenClaw runtime to run multi-agent workflows, built-in skills, MCP integrations, and IM remote control (WeChat, Feishu, Telegram, etc.).