Discover the Best AI Resources
Curated essentials, no noise — just what matters
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.
Provides a lightweight build platform for HIP and ROCm that supports building ROCm, PyTorch, and JAX from source, multi-architecture nightly releases, and integrated CI/CD and developer tooling for Linux and Windows.
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.
Continuously captures your screen and spoken conversations, transcribes them in real time, generates summaries and action items, and exposes a memory-backed chat that can retrieve what you've seen and heard. Works across desktop, mobile and wearable devices and supports local SDKs and cloud sync.
End-to-end framework for running and reproducing foundation-model research workflows — from data curation and tokenization to training and evaluation. Emphasizes reproducibility by recording every step (including failed runs) and expressing experiments as dependency-ordered steps.
Generates Wikipedia-style articles from web search using LLMs: it researches topics, produces multi-perspective outlines via perspective-guided question asking and simulated conversations, then drafts full articles with citations. Supports human-AI collaboration (Co-STORM) and grounding with multiple retrievers.
SDK for building browser-based AI agents: expose Playwright-style APIs plus natural-language primitives (act/observe/extract) with self-healing actions, token-efficient accessibility trimming, and runtime extension next to the browser. Supports TypeScript, Python, and Go.