Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides 1,000,000 model-generated chain-of-thought traces and instruction–response pairs for fine-tuning and distilled supervision. Focused splits (coding, PHD-Science, General-Math, MultilingualSTEM), ~5B tokens, Apache-2.0 license.
Runs the Bonsai family of quantized LLMs locally (including vision-capable 27B): provides scripts and demo UIs to run 1-bit and ternary Bonsai models on macOS (Metal), Linux/Windows (CUDA/Vulkan/ROCm), or CPU, with long context, tool-calling and an optional Open WebUI agent demo.
Provides a unified 615k-hour English speech corpus for TTS training, aggregating 11 public datasets and web-sourced recordings into 16 kHz Opus WebDataset shards. Includes a quality-filtered core subset (510.1k hours), metadata splits, and mixed licenses across sources.
Compresses high-dimensional embeddings into low-bit TurboQuant indexes for fast, memory-efficient local vector search. Supports online ingest (no train/rebuild), SIMD kernels that match or beat FAISS, per-vector length-renormalization, and runtime allowlists — suited for privacy-sensitive, low-latency RAG.
Turns a domain description into a Claude Code agent team and the skills they use — auto-generates agent definitions and skill files from six pre-defined team-architecture patterns. Best for teams building structured multi-agent workflows on Claude Code.
Runs and monitors AI agents inside real terminal panes, surfacing agent state (blocked / working / done) and keeping agents persistent across detach/reattach. Offers workspaces, tabs, panes, socket-API integrations, and a single Rust binary for macOS/Linux.
Orchestrates end-to-end video production with agentic pipelines that research, script, generate assets, edit, and render finished videos. Distinguishes itself by supporting true real-footage retrieval (Archive.org, NASA, Wikimedia), Remotion/HyperFrames composition, and usable zero-key workflows alongside cloud providers.
Bridges an LLM assistant to your locally running TradingView Desktop via Chrome DevTools Protocol for AI-assisted chart analysis, Pine Script development, and UI automation. Key features: Claude Code MCP integration, a JSON/CLI 'tv' toolset, local-only operation and streamable chart data.
Provides 3,000+ hours (≈611K utterances) of transcribed 16 kHz multi-dialect Arabic speech across 13 dialects for ASR and spoken-dialect identification. Transcripts preserve dialectal orthography (partial diacritics); the train split is ~337 GB in parquet, so streaming is recommended.
Curated collection of resources, patterns, and reference implementations for building reliable AI agent harnesses—covering context delivery, tool/MCP design, memory, permissions, observability, verification, and orchestration for production agent engineering.
Provides multi-turn agent trajectories with real tool executions and explicit <think> reasoning blocks for training and evaluating tool-calling agents. Contains two model-sourced configs (Kimi-K2.5, GLM-5.1) totaling ~14.7K samples — useful for SFT, agent-skill research, and tool-integration experiments.