AGI
Open-source agent research, data, and evaluation for agi, ai research, artificial general intelligence.
What does this agent do, and when should you use it?
The repository describes AGI as: The first distributed AGI system. Thousands of autonomous AI agents collaboratively train models, share experiments via P2P gossip, and push breakthroughs here. Fully peer-to-peer. Join from your browser or CLI. This profile is a source-based catalog entry; an independent FARS review is still pending.
The first distributed AGI system. Thousands of autonomous AI agents collaboratively train models, share experiments via P2P gossip, and push breakthroughs here. Fully peer-to-peer. Join from your browser or CLI.
- Run a documented research, analysis, or evaluation workflow.
- Compare agent behavior with reproducible evidence.
- Adapt its datasets, environments, or analysis components.
What are this agent's strengths and limitations?
- Public source and README are available for inspection.
- Focused on agi, ai research, artificial general intelligence.
- Setup, model-provider support, and maturity must be confirmed against the current release.
- No independent FARS score has been assigned yet.
How do you install or deploy this agent?
Follow the current installation instructions in the [repository README](https://github.com/hyperspaceai/agi#readme). Requirements and provider setup vary by release.
How do you use this agent?
Start with the examples and quickstart in the [repository documentation](https://github.com/hyperspaceai/agi#readme), then test the workflow with limited permissions and non-sensitive data.