autonomous-ai/autonomous-grid

Tiles

A local-first, collaborative AI assistant that works for you. Built with open models and decentralized protocols.

AI agent runs amok in Fedora and elsewhere

Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]

Networked Intelligence: Active Shared Context Graphs for Human-AI Team Science

Most AI-for-science systems focus on scaling a single reasoning process by using better models, larger context windows, long-horizon agentic execution, or digital co-scientists working with one principal user. However, challenging scientific problems are rarely solved by one reasoner alone. They are solved by teams whose members carry different priors, experimental background, tacit knowledge, and domain-trained intuitions. The open problem is therefore not only how to scale models, but how to develop "networked intelligence", scaling the connections between humans and AI systems so that a result or hypothesis produced in one context reaches another person, agent, instrument or robot that can act on it. We introduce Mycelium, an active shared workspace that automatically connects researchers and AI agents. As human users and agents work, the system captures important observations and hypotheses, tracks how they relate to the team's evolving knowledge model, and routes them to the person or agent whose next decision they can inform. We evaluate Mycelium through a real-world scientific discovery use case: a biological multi-omics campaign where shared context turned a local analytical finding into a cross-expert mechanistic constraint and ultimately into an experimental design. Finally, we describe networked intelligence as sparse conditional computation over distributed scientific contexts. This framework establishes when a scaled standalone agent is sufficient, and when isolated data and specialized expertise make a networked approach essential.

Environments Hub: A Community Hub To Scale RL To Open AGI

RL environments are the playgrounds where agents learn. Until now, they’ve been fragmented, closed, and hard to share. We are launching the Environments Hub to change that: an open, community-powered platform that gives environments a true home.Environments define the world, rules and feedback loop of state, action and reward. From games to coding tasks to dialogue, they’re the contexts where AI learns, without them, RL is just an algorithm with nothing to act on.

MOSAIC — Modular Open Science, AI & Collective Intelligence

MOSAIC is an R&D program to build a new medium for large-scale, AI-augmented networked research.

Helicone/ai-gateway

The fastest, lightest, and easiest-to-integrate AI gateway on the market. Fully open-sourced.

Tiles: A private, collaborative AI assistant that works for you.

A private, collaborative AI assistant that works for you. Built with local models and AT Protocol.

SambaNova | The Fastest AI Inference Platform

Discover SambaNova - the complete AI platform delivering the fastest AI inference, fine-tuning, and scalable solutions for agentic AI easily integrated into existing data center infrastructures.

AI for the rest of us - The AI community for everyone

Our community and events are for everyone. We're a community of AI practitioners, educators, students, and enthusiasts who are passionate about making AI accessible to everyone.

Hyperspace — Decentralized AI Agent Network

Run an autonomous AI agent on the decentralized P2P network. Earn points, serve inference, and contribute to distributed ML research.

Together AI | The AI Native Cloud

Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.

AI Analytics Platform for Your Whole Team

Agentic notebooks, conversational self-serve, and Context Studio for governed AI answers — all in a unified platform for your whole team.

Artificial intelligence

Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1]

Cloudflare Workers AI | Open-source AI inference

Workers AI facilitates the scalable development & deployment of AI applications at the edge.