Reinforcement Learning with OpenEnv - AI Build & Learn #3
Details
Welcome to AI Build & Learn a weekly AI engineering stream where we pick a new topic and learn by building together.
This event is about Reinforcement Learning with OpenEnv. OpenEnv is a e2e framework for creating, deploying and using isolated execution environments for agentic RL training, built using Gymnasium style simple APIs.
https://github.com/meta-pytorch/OpenEnv
Resources
- GitHub: https://github.com/sagecodes/ai-build-and-learn
- Events Calendar: https://luma.com/ai-builders-and-learners
- Slack (Flyte AI Slack): https://slack.flyte.org/
- Hosted by Sage Elliott: https://www.linkedin.com/in/sageelliott/
In this stream
- Reinforcement Learning with OpenEnv
- Hands-on demo
- Community Discussion + practical examples
Community challenge (optional)
Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.
Note on Flyte / Union
You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.
- Union: https://www.union.ai/
- Flyte: https://flyte.org/
Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).