Chakra Labs
151 posts
High-fidelity trajectories and environments for frontier AI research
- Thanks for featuring our work @immutablejacob, @MessariCrypto, and team! Better datasets & environments => better modelsDespite the incoming drought of public text, we're nowhere close to using up the world's data. The world's total data is ~200 ZBs and doubles every ~2 years. The valuable modalities and sources that can be drawn from include: > Audio (@psdnai, @silencioNetwork, @Meet_Perle) >
- Replying to @chakra_aiTo get started, check out our docs and code examples below.
- Replying to @chakra_aiEx: access our Amazon clone using familiar Gymnasium style APIs.
00:00 - Replying to @chakra_aiNow, you can access any Dojo clone using the same APIs leveraged by OpenEnv.
- Replying to @chakra_ai @huggingface and @PyTorchOpenEnv is a community framework developed by @huggingface, @PyTorch, and others for creating, deploying, and using isolated execution environments for agentic RL training.
- Chakra Labs repostedYou can now run tasks in @chakra_ai's RL environments using Browserbase as the runtime. Get task concurrency, isolated contexts, and enhanced observability.Update: Dojo now supports @browserbase
00:00 - Replying to @chakra_aiTo get started with this custom run-time, check out the Dojo engine docs below:
- Replying to @chakra_aiWe're excited to announce support for Browserbase, which allows researchers to quickly spin up 1000's of browser tasks concurrently using their serverless hosted infrastructure. Researchers now benefit from: - Hyper-scalable browser infra - Secure SOC II instances - Native













