Ray RLlib

Ray Train

Ray Datasets

RayDP

Retail

Gaming

Government

Financial

Ray Serve

Anyscale

Ray Core

Healthcare

Technology

Ray Roadshow

Here you can find where the Anyscale and Ray teams will be in attendance at industry events across the globe. 

Industry Event

Press Interview

On-Demand Webinar

Webinar

RL Summit

Weekly Demo

Ray Meetup

Anyscale GA Launch

Anyscale Academy provides training on the Ray ecosystem, tailored for data scientists, data engineers, and MLOps engineers.

Anyscale Academy Logo

Anyscale Academy

Ray Summit brings together the community of architects, machine learning engineers, researchers, and other developers building the next generation of scalable, distributed, high-performance Python and machine learning applications. The conference will include those who are already using Ray platform and those who are interested in learning how Ray can meet their needs.

Ray Summit

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Roger Ng, M.D.

Roger Ng, M.D., Cardiologist, Virginia Mason Heart Institute

The Journey from AI to Bedside: Translating Academic Research to Serving Patients Using Ray

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Alex Wu

A Deep Dive into Ray’s Scheduling Policy

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Stanley Bishop

Stanley Bishop-Rosal

Stanley Bishop, Head of Data Science, Drift Biotechnologies

Machine Learning and Microbiology in the Cloud Through Ray

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Linsong Chu

Linsong Chu, Research Engineer, IBM Research

Anomaly Detection on Remote Sensing with Ray + Horovod

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Edward Junprung

Sahar Esmaeilzadeh

Edward Junprung (Customer Success) & Sahar Esmaeilzadeh (Lead Simulation Engineer), Pathmind

Applying Ray and RLlib to Real-life Industrial Use Cases

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Wei Chen

Wei Chen, Deep Learning Software Engineer, NVIDIA

Large Scale Data Loading and Data Preprocessing with Ray

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Raghu Ganti

Raghu Ganti, Principal Research Staff Member, IBM

Scaling and Unifying SciKit Learn and Spark Pipelines using Ray

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Peter Noseworthy, M.D.

Peter Noseworthy

Peter Noseworthy, M.D., Professor, Mayo Clinic College of Medicine | Cardiologist (Cardiac Electrophysiology) Director, Heart Rhythm and Physiologic Monitoring Laboratory, Mayo Clinic

How Smart is the ECG? Lessons from Advanced ECG Analytics

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Hao Zhang

Collective-on-Ray: High-performance Collective Communication for Distributed Machine Learning on Ray

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Melih Elibol

Melih Elibol, Graduate Researcher, UC Berkeley

NumS: Scalable Array Programming for the Cloud

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Tanja Bayer

Tanja Bayer, Machine Learning Engineer, Widas Technologie Services GmbH

Leveraging the Possibilities of Ray Serve in Implementing a Scalable, Fully Automated Digital Authentication Service

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 Nicolas Hohn

A deeper dive into Nic Hohn's keThe increasing prevalence of high-fidelity industrial digital twins is providing a range of opportunities to apply Reinforcement Learning (RL) techniques outside of traditional academic examples and video games. We will present how McKinsey supported Emirates Team New Zealand in winning the 36th America’s Cup by leveraging some of the latest AI techniques and technology platforms. The America’s Cup is the oldest sports trophy in the world, but is first and foremost a technology competition. It’s a race against time to design, test, and deliver the fastest yacht on race day, with a team of Olympic-level athletes ready to sail it and make it fly thanks to cutting-edge hydrofoils. We will describe how we used deep Reinforcement Learning to speed up their design process. In particular, we will deep dive on the underlying technologies we used, from scaling RL training on a Ray cluster, to using Tune to manage results variability.ynote, "Making Boats Fly with AI on Ray". 

Deeper Dive on Making Boats Fly with AI on Ray

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Dr. Charles He

Dr. Charles He, Chief Architect of Computing and Storage, Ant Group

Fusion Computing at Ant Group

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Marvin Theimer

Marvin Theimer, Distinguished Engineer, Amazon Web Services

Cloud Computing Made Better: An AWS View on Serverless Computing

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Matt Johnson

Matt Johnson, Research Scientist, Google Brain | Tech Lead, JAX

JAX: Accelerated Machine Learning Research via Composable Function Transformations in Python

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Dawn Song

Dawn Song 2

Towards Building a Responsible Data Economy

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Tianqi Chen

Tianqi Chen, Assistant Professor, ML & CS Department, Carnegie Mellon University | CTO, OctoML | Creator of Apache TVM, XGBoost, and the co-creator of Apache MXNet

Elements of Learning Systems

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Eric Brewer

Eric Brewer, VP Infrastructure & Google Fellow, Google | Professor, UC Berkeley

Lessons from the Kubernetes Adventure

A one stop shop for all events, past and future, to connect and learn from the global community of Ray experts.

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How Torc Robotics Scales Multimodal AI for Autonomous Driving with Ray

Building a Multimodal Video Processing Pipeline with Ray

Multimodal data - Architecting pipelines that don’t break at scale

Multimodal data: Architecting pipelines that don’t break at scale

Hands on Workshop Scaling Vision-Language-Action (VLA) Models with Ray

Hands on Workshop: Scaling Vision-Language-Action (VLA) Models with Ray

Live Virtual Hands On Lab: Distributed Training at Scale with Ray and PyTorch

From Prototype to Production: Securely Accelerating Physical AI with Vision-Language-Action (VLAs) Models

Promotional webinar graphic from Anyscale on a black background. Text reads ‘Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray.’ The date and times are shown as Feb 19, 8:30 AM PT, 11:30 AM ET, and 5:30 PM CET. The Anyscale logo appears at the top left with the word ‘Webinar’ at the top right. At the bottom left is a headshot of Suman Debnath, labeled Principal Developer Advocate at Anyscale.

Webinar: Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

Scaling LLM Fine-Tuning with FSDP, DeepSpeed, and Ray

This section is used to order the "Types" and "Tags" that show up for filters on the Event Index

Event Types

All Products / Libraries

Visit Anyscale at Microsoft Build, Booth G201, June 2-3: 

Powered by Ray, Anyscale empowers AI builders to run and scale all ML and AI workloads on any cloud and on-prem.

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Events