Abstract: Developers and data scientists used to have a tough choice between easy-to-use but inflexible AI developer services and powerful ML platforms with steep learning curves. Today, there’s an increasing shift to large models like OpenAI’s GPT-3 and Codex. These models are trained once and then applied flexibly to a wide variety of downstream applications. OpenAI’s API lets all builders, from non-developers to ML experts, go from building a compelling prototype in 5 minutes to scaling customized models to production-level loads. It’s used by thousands of companies to transform existing products and to build entirely new application experiences.
Bio: Peter Welinder is VP of Product and Partnerships at OpenAI. He leads commercialization of OpenAI’s research, including OpenAI's GPT-3 and Codex API and the Github Copilot partnership. Previously, he founded and led applied machine learning engineering and product at Dropbox. He was co-founder and CEO of Anchovi Labs (acquired by Dropbox). Peter has a PhD in Computation and Neural Systems from Caltech and a degree in Physics from Imperial College London.