ASPIRE is a new type of continual learning: "training" is skill refinement instead of gradient descent.
Global
Reef is the first open-source infrastructure for continual self-improving agents. It connects agent inference, feedback, learning, and versioned delivery. Use it to train model weights with Slime and SGLang, or improve an agent's harness, including its prompts, rules, and skills.
Cadence's goal is a continuing learning system with the flexibility of animal and human problem solving: acquiring skills from experience, retaining useful knowledge, imagining alternatives and creating solutions across domains.
mini-AGI - is a continual learning byte-level language model that assembles its own architecture, trains from scratch on a single 8 GB VRAM GPU, and keeps learning from everything it reads.
MetaClaw is an agent that meta-learns and evolves in the wild.