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Prime RL now supports expressing and training multi-agent systems, enabling use cases like agentic judge, self-play, user simulation, and complex agent collaboration.
Prime Intellect Lab is out of beta, offering a platform to train models with support for various architectures and modalities, enabling self-improving agents.
Andrej Karpathy frames LLM training as text, conversations, and environments; Prime Intellect's Verifiers is an open-source framework for building and sharing RL environments for LLMs, released under MIT license, with a hub of 2500+ environments.
Prime Intellect raises $130M Series A to help enterprises build their own AI agents.
Prime Intellect has raised $130 million in Series A funding at a $1 billion valuation to provide enterprises with a full-stack platform for building their own AI agents, offering compute access, reinforcement learning tools, and evaluation capabilities as a marketplace.
Prime-rl adds a first-class algorithms layer with six built-in RL algorithms (GRPO, MaxRL, OPD, OPSD, SFT, ECHO), making it easier to implement custom algorithms with a single file.
A researcher announced they have joined PrimeIntellect to work on continual learning.