Jeff Boudier

Jeff Boudier Product Director Hugging Face Conference Video https://youtube.com/watch?v=c48skkWNARg%3Fsi%3D9zWdP9AdVjsd0UYd Slides Presentation Title: Building LLM and Generative AI applications with open source and Hugging Face Presentation Summary: In this presentation, Jeff Boudier will walk you through the latest open source models and libraries you can use to build LLM and Generative AI applications using your own […]

Sarah Wooders

Sarah Wooders PhD Skyplane Conference Video https://youtube.com/watch?v=EXC25u_qJqY%3Fsi%3DTugnfTzbHaZebSpR Slides Presentation Title: Skyplane Fast and Cheap Data Sharing across the Cloud(s) Presentation Summary: We present Skyplane, an open-source project from UC Berkeley for blazing fast object store transfers within and between clouds.  Skyplane is faster and lower-cost than existing data transfer systems with universal support across clouds. […]

Mia Garrard

ML platforms help enable intelligent data-driven applications and maintain them with limited engineering effort. Upon sufficiently broad adoption, such platforms reach economies of scale that bring greater component reuse while improving efficiency of system development and maintenance. For an end-to-end ML platform with broad adoption, scaling relies on pervasive ML automation and system integration to reach the quality we term self-serve; a quality we define with ten requirements and six optional capabilities. 

Peter Norvig

Recently, Large Language Models have shown a strong ability to generate working code. This talk explores what this means for the future of programmers, programming languages, and the software industry.

Harrison Chase

Harrison Chase Co-Founder and CEO Langchain Conference Video https://youtube.com/watch?v=q3RGQ0_yJEk%3Fsi%3DiZ3vR0_Si5IX0xqX Slides Presentation Title: Building reliable LLM applicationswith LangChain and LangSmith Presentation Summary: It’s become easier and easier to build a prototype for an LLM application – with LangChain you can do it in ~5 lines of code. But going from prototype to production is much more […]

Alex Chao

In the short time that large language models have gone mainstream, we’ve started to see several patterns that AI researchers and developers have used to build their products. These include things like prompt engineering, prompt templating, chain of thought, vectorized memory and embeddings, and more. They’ve enabled new forms of natural language-based apps and have truly opened people’s imagination to what is possible with AI.