Discover the Best AI Resources
Curated essentials, no noise — just what matters
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.
Provides a multilingual, deduplicated corpus of public source code in Parquet for large-scale model training and evaluation. Includes license metadata, language splits, and streaming-friendly packaging for use with Hugging Face Datasets — suited to training code-focused foundation models but requires careful license/provenance review.
Memory engine that lets AI apps remember users across conversations: it extracts facts, tracks updates, resolves contradictions, and auto-forgets stale info, returning context in ~50ms. Tops the LongMemEval, LoCoMo and ConvoMem memory benchmarks.
Automates browser workflows using LLMs and computer vision instead of XPath selectors, so it works on unseen sites and survives layout changes. Drive tasks with natural-language prompts: act, extract, validate. Handles 2FA and multi-step flows.
Generates HD short videos from a single topic/keyword — auto-creates script, finds/assembles footage, generates subtitles, TTS and background music. Offers web UI + API, batch mode, multiple LLM/TTS providers and common short-video aspect ratios.
Open-weights 314B-parameter Mixture-of-Experts language model (8 experts, 2 active per token, 8,192-token context) released under Apache 2.0. Ships a raw JAX checkpoint plus reference inference code; needs heavy multi-GPU memory to load.
Generates short videos from text, images, or videos and ships a full training/inference pipeline with checkpoints and demos. Key features include multi-stage training (VAE / 3D-VAE), rectified-flow training, video compression modules, and support for 2s–16s clips at up to 720p. Best for researchers and engineers who can provide substantial GPU resources.
Orchestrates low-code multi-agent teams that plan, research, code and deliver results to Telegram, Discord, and WhatsApp. Includes handoffs, guardrails, memory and RAG, and integrates 100+ LLM providers via MCP for production-ready agent workflows.
Runs coding agents and automations from a self-hosted developer control center, with local, remote, cloud, and ACP-compatible backends for managed engineering workflows.