We were inspired to build Spinning Up through our work with the OpenAI Scholars⁠(opens in a new window) and Fellows⁠(opens in a new window) initiatives, where we observed that it’s possible for people with little-to-no experience in machine learning to rapidly ramp up as practitioners, if the right guidance and resources are available to them. Spinning Up in Deep RL was built with this need in mind and is integrated into the curriculum for 2019 cohorts⁠(opens in a new window) of Scholars and Fellows.

We’ve also seen that being competent in RL can help people participate in interdisciplinary research areas like AI safety⁠(opens in a new window), which involve a mix of reinforcement learning and other skills. We’ve had so many people ask for guidance in learning RL from scratch, that we’ve decided to formalize the informal advice we’ve been giving.

Spinning Up in Deep RL is part of a new education initiative at OpenAI which we’re ‘spinning up’ to ensure we fulfill one of the tenets of the OpenAI Charter⁠(opens in a new window): “seek to create a global community working together to address AGI’s global challenges”. We hope Spinning Up will allow more people to become familiar with deep reinforcement learning, and use it to help advance safe and broadly beneficial AI.

We’re going to host a workshop on Spinning Up in Deep RL at OpenAI San Francisco on February 2nd 2019. The workshop will consist of 3 hours of lecture material and 5 hours of semi-structured hacking, project-development, and breakout sessions - all supported by members of the technical staff at OpenAI. Ideal attendees have software engineering experience and have tinkered with ML but no formal ML experience is required. If you’re interested in participating please complete our short application here⁠(opens in a new window). The application will close on December 8th 2018, and acceptances will be sent out on December 17th 2018.