Join us for our first South Bay event of the year!
If you've ever worked on a Gen AI project in the real world (or want to), you're probably aware that just getting it to work in production is half the battle. Partnering with Outerbounds, we will be having an evening of engaging speakers who will share real life Gen AI "war stories".
Our Speakers
Savin Goyal: Savin is the cofounder and CTO of Outerbounds, where his team is building human-friendly infrastructure to accelerate the adoption of machine learning and AI at major enterprises like Amazon, Netflix, Goldman Sachs, and more. He will be speaking on best practices towards productionizing Gen AI workflows, complemented by real world examples from different industries and domains.
Jineet Doshi: Jineet is a Staff Data Scientist at Intuit with extensive experience building and deploying NLP and large language models. He also holds multiple patents in NLP and has given guest lectures at Stanford University. His talk, titled "Measuring the Minds of Machines: Evaluating Generative AI Systems", will focus on the different approaches towards evaluating LLMs.
Chandan Maruthi: Chandan is the co-founder and CEO of Twig.so, an AI Agent Assist platform. Previously, he has built Data and AutoML products at H2O.ai and E2Open. He will be speaking about end-to-end RAG workflows in production, including what works well today, what doesn't work, and areas of research required to improve AI accuracy over time.
Agenda
- 5:45pm: Doors open
- 6:15pm: Greetings!
- 6:30pm: Presentations begin
- 8:00pm: Meet and mingle with our speakers
Special thanks to Plug and Play for being an amazing venue partner and hosting this event!
Please be advised: Unfortunately, space is quite limited at these community events and we can not always accept everyone we would like to. If you are not accepted to this event, please keep applying! We appreciate your application tremendously and we are looking forward to seeing you at a future event very soon!
MLOps Communityfills the swiftly growing need to share real-world Machine Learning Operations best practices from engineers in the field. While MLOps shares a lot of ground with DevOps, the differences are as big as the similarities. We needed a community laser-focused on solving the unique challenges we deal with everyday building production AI/ML pipelines. We’re in this together. Come learn with us in a community open to everyone. Share knowledge. Ask questions. Get answers.
Outerboundsisbuilding the modern ML infrastructure stack with Metaflow, a human-friendly and open-source framework for easy design and development of ML apps.
