​Welcome to ML-at-Scale '24! Hosted by the HPE Open Source Community team, this event is the leading event for at-scale machine learning.

​Building off the buzz from ML-at-Scale ‘23, we’re excited to double-down and meet you all in person this Fall. ML-at-Scale ‘24, in collaboration with MLOps Community, will be held in the Bay Area on October 30. Food and drink provided by our gracious hosts. You can register here for the virtual stream or for the in-person event at the link below:

🎙️ Our Speakers

​Jimmy Whitaker AI/ML Product Manager, HPE

​Chinar Movsisyan - CEO, Feedback Intelligence

​Sonam Gupta, PhD - DevRel, aiXplain

​Scaling LLM Deployments: Model Onboarding, Evaluation, and Benchmarking

​In this talk, we’ll dive into the essential workflows for deploying large language models (LLMs) at scale, covering model onboarding, evaluation, and benchmarking using LLMPerf. Learn how to assess model performance and compare benchmarks. We’ll share insights into the tools and best practices used at aiXplain.com, with a focus on practical, scalable solutions.

​

​​​📆 Agenda

​5:00: Doors Open

​5:00 - 5:30 : Networking

​5:30 - 6:15 : Speaker Sessions

​6:15 - 7:30 : Networking, Costume Prize Giveaway

​​​​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 Community fills 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.