Extending Context Window in AI Models

Today we have Mark Huang on the show. Mark has previously held roles in Data Science and ML at companies like Box and Splunk and is now the co-founder and chief architect of Gradient, an enterprise AI platform to build and deploy autonomous assistants.

In our chat, we get into some of the stuff he’s seeing around autonomous AI agents and why people are so excited about that space. Mark and his team has also recently been working on a project to extend the Llama-3 context window. They were able to extend the model from 8K tokens all the way to 1 million through a technique called theta-scaling. He walks us through the details of this project and how longer context windows will impact the types of use cases we can serve with LLMs.

Follow Mark: https://x.com/markatgradient

Follow Sean: https://x.com/seanfalconer