Using Large Language Models at AngelList
Speakers

Thibaut LaBarre is an engineering lead with a background in Natural Language Processing (NLP). Currently, Thibaut focuses on unlocking the potential of Large Language Model (LLM) technology at AngelList, enabling everyone within the organization to become prompt engineers on a quest to streamline and automate the infrastructure for Venture Capital.
Prior to that, Thibaut began his journey at Amazon as an intern where he built Heartbeat, a state-of-the-art NLP tool that consolidates millions of data points from various feedback sources, such as product reviews, customer contacts, and social media, to provide valuable insights to global product teams. Over the span of seven years, he expanded his internship project into an organization of 20 engineers.
He received a M.S. in Computational Linguistics from the University of Washington.

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

From serving as an officer in the US Navy to Consulting for some of America's largest corporations, Ryan has found his passion in the enablement of Data Science workloads for companies and teams.
Having spent years as a data scientist, Ryan understands the types of challenges that DS teams face in scaling, tracking, and efficiently running their workloads.
SUMMARY
Thibaut innovatively addressed previous system constraints, achieving scalability and cost efficiency. Leveraging AngelList investing and natural language processing expertise, they refined news article classification for investor dashboards. Central is their groundbreaking platform, AngelList Relay, automating parsing and offering vital insights to investors. Amid challenges like Azure OpenAI collaboration and rate limit solutions, Thibaut reflects candidly. The narrative highlights prompt engineering's strategic importance and empowering domain experts for ongoing advancement.

