Who Attends Ray Summit?

Being able to operate quickly at this massive scale has enabled us to deliver novel solutions towards Dendra Systems’ mission of scaling ecosystem restoration of our biodiverse natural world.

We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business.

At OpenAI, we are tackling some of the world’s most complex and demanding computational problems. Ray powers our solutions to the thorniest of these problems and allows us to iterate at scale much faster than we could before. As an example, we use Ray to train our largest models, including ChatGPT.

Ray and Anyscale empower even the leanest teams to bring AI to production and realize the business potential of AI in record time.

Ray and Anyscale have enabled us to quickly develop, test and deploy a new in-game offer recommendation engine based on reinforcement learning, and subsequently serve those offers 3X faster in production. This resulted in revenue lift and a better gaming experience.

Being able to operate quickly at this massive scale has enabled us to deliver novel solutions towards Dendra Systems’ mission of scaling ecosystem restoration of our biodiverse natural world.