A member-governed cooperative for AI inference. Direct the models, the values, and the direction — together.
co/core · 5.0 ★ | at-store
co/core is a cooperative for AI inference — people pooling the Macs they already own to run open models for each other. Tag: Developer.
co/core — an AI cooperative
co/core is a cooperative for AI inference — people pooling the Macs they already own to run open models for each other, instead of renting from the big clouds. An experiment in AI infrastructure we build, share, and own together. Bring your existing OpenAI-compatible code, or share a Mac and help run it.
co/core — an AI cooperative
co/core is a cooperative for AI inference — people pooling the Macs they already own to run open models for each other, instead of renting from the big clouds. An experiment in AI infrastructure we build, share, and own together. Bring your existing OpenAI-compatible code, or share a Mac and help run it.
co/core — an AI cooperative
co/core is a cooperative for AI inference — people pooling the Macs they already own to run open models for each other, instead of renting from the big clouds. An experiment in AI infrastructure we build, share, and own together. Bring your existing OpenAI-compatible code, or share a Mac and help run it.
Public AI Inference Utility
A nonprofit, open-source service to make public and sovereign AI models more accessible.
autonomous-ai/autonomous-grid
Your AI intranet: network the computers you already own for inference and training.
An inference cooperative for academic AI – Writings and rehearsals by Nathan Schneider
Universities, like other institutions, are currently being confronted with a dilemma: embrace the AI tools currently available from big-name tech companies, and be part of the future, or reject the miraculous machines and stick your head in the sand. This dilemma is a false one, on several counts. It is far from clear what role generative AI will have in the future of academic life, for one thing. And beyond rewording the choices, surely there are other options that this dilemma fails to consider.
Private inference
When you use an AI service, you’re handing over your thoughts in plaintext. The operator stores them, trains on them, and–inevitably–will monetize them. You get a response; they get everything.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Notion | Where teams and agents work together
A collaborative AI workspace, built on your company context. Build and orchestrate agents right alongside your team's projects, meetings, and connected apps.
Reflections on the Cooperative AI Conference | Platform Cooperativism Consortium
I am just returning from our conference on Cooperative AI in Istanbul. Part of what I love about conferences—what keeps me doing this, convening these global PCC events —is meeting people who are both…
