Introduction to Text and Code Embeddings in the OpenAI API | TransformX 2022

Text embeddings are useful features in many applications including semantic search, predicting code completion, natural language, topic modeling, classification, and computing text similarity. Arvind Neelakantan, Research Lead and Manager at OpenAI, will introduce the concept of embeddings, a new terminus in the OpenAI API.
When OpenAI originally introduced the API two years ago, it was based on the GPT-3 model, which was useful for many tasks. But, as Neelakantan will explain, GPT-3 is not explicitly optimized to produce a single vector or embedding of the input. This ability, to have a condensed representation of the input, would be helpful for programmers and others to use as features for downstream applications, the OpenAI team determined. They set about building an unsupervised model that is good at getting this kind of single embedding, and created a contrastive pre-training model, which Neelakantan will describe. He will also cover use cases for embeddings, and how the API is used in the real world, including at JetBrains Research for astronomical research and at FineTune Learning, which builds education systems. FineTune is using text embeddings to more accurately find textbook content based on learning objectives.
👉 Check out more here: scl.ai/3gt4WhZ

[@mohajeramir]

We are lucky to live in a day and age when you can hear from the creators on demand.

[@husambarham3779]

just his eyes say what he has done to humanity

[@itsmeben604]

Thank you for this. I don't follow everything, but I understand more than before. I suggest going to a Toastmasters meeting once a month for a little while though. It's hard to listen and follow with all of the "aahh"s and "umm"s. It doesn't take much practice with a group of skilled people to rid yourself of this habit, which will improve your speaking ability exponentially. Thanks again for providing us with this detailed, but still somewhat high level talk. It must be hard to simplify such a complex topic any more than you have.

[@Kube4x]

I’m sorry but I’m 7 minutes in and nothing makes sense. We need this simplified. Thanks