Conferences / Ray Summit
Ray Summit 2023
Sep 18–20, 2023 · San Francisco Marriott Marquis, San Francisco, CA, United States
- Conference
- Ray Summit Vendor & industry
- Dates
- Sep 18, 2023 – Sep 20, 2023
- Venue
- San Francisco Marriott Marquis
- Place
- San Francisco, CA, United States
- Format
- In person
- Status
- Past
- Attendance
- —No figure; Anyscale's event page says only 'Every year, thousands of Ray fans come together at Ray Summit.'
- Website
- raysummit.anyscale.com
- Recorded
- 12 sponsors · 141 speaker appearances
- Notes
- Billed as 'The LLM and Generative AI Conference for Developers'. Conference 18-19 Sep, hands-on training day 20 Sep. Venue: official hotel page (Marriott Marquis, 780 Mission St) and agenda room names (Yerba Buena salons, Golden Gate ballroom). Speakers: full agenda from the 6 Sep 2023 snapshot (~138 speakers; training-day instructors not included). Sponsors: the sponsors page (raysummit23.anyscale.com/sponsors) is no longer online and was not archived; tiers taken from its search-engine text, which named Platinum and Gold in full but only three of the Silver sponsors. Ticket prices not found.
Ticket prices
No ticket prices recorded
Sponsors 12
Speakers and talks 141
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Albert Greenberg | Uber | Keynote | — | — |
| Ben Horowitz | Andreessen Horowitz | Keynote | — | — |
| Brian McClendon | Niantic | Keynote | — | — |
| Evan Cox | Netflix | Keynote | — | — |
| Hien Luu | DoorDash | Keynote | — | — |
| Ion Stoica | Anyscale | Keynote | — | — |
| John Schulman | OpenAI | Keynote | — | — |
| Robert Nishihara | Anyscale | Keynote | — | — |
| Ya Xu | Keynote | — | — | |
| Zhitao Li | Uber | Keynote | — | — |
| Adel El Hallak | NVIDIA | Speaker | Easily Scale to Production-Ready Generative AI with NVIDIA and Anyscale | — |
| Ahmad Shadid | Antbit.io | Speaker | Decentralized Ray - Scaling Ray for Global Inference | — |
| Alex Corvin | Red Hat | Speaker | Automatically scaling the execution of Foundation Models workflows: Ray with CodeFlare and Red Hat OpenShift Data Science Pipelines | — |
| Alex Remedios | treebeardtech | Speaker | Forecasting Covid Infections for the UK's National Health Service using Ray and Kubernetes | — |
| Ali Arsanjani | Speaker | Integrating Ray.io into the Google Cloud Ecosystem for the Enterprise | — | |
| Ali Arsanjani | Speaker | Making your Enterprise GenAI Ready and GenAI Enterprise Ready | — | |
| Ali Kanso | Microsoft | Speaker | The Different Shades of using KubeRay with Kubernetes | — |
| Ali Naqvi | Speaker | Inference Graphs at Linkedin Using Ray-Serve | — | |
| Allen Wang | Speaker | Developing Ray Applications on Google Cloud TPUs | — | |
| Ameer Haj Ali | Anyscale | Speaker | Train and Deploy LLM/Generative AI Application Cheaper, Faster and Safer with Anyscale’s Infrastructure | — |
| Amog Kamsetty | Anyscale | Speaker | Faster and Cheaper Offline Batch Inference with Ray | — |
| Amog Kamsetty | Anyscale | Speaker | How Anyscale Speeds up ML Data Processing with Ray | — |
| Anish Shah | Weights & Biases | Speaker | Tend and Tune Your MARL Experiments with Ray and Weights & Biases | — |
| Anshumali Shrivastava | ThirdAI Corp | Speaker | Scaling up Terascale Deep Learning on Commodity CPUs with ThirdAI and Ray | — |
| Apoorva Kulkarni | Amazon Web Services | Speaker | Unleashing the Power of GenAI: Scaling with Ray and Orchestrating with Kubernetes | — |
| Archit Kulkarni | Anyscale | Speaker | KubeRay: A Ray cluster management solution on Kubernetes | — |
| Atin Sood | IBM | Speaker | How to simplify execution of cloud-native model training and validation with CodeFlare: A Hands-On Demo | — |
| Azul Garza | Nixtla | Speaker | TimeGPT: A Foundation Large Time Series Model | — |
| Ben Wilson | Databricks | Speaker | Ray on Spark | — |
| Bo Ling | Uber | Speaker | Enabling End-to-End LLMOps on Michelangelo with Ray | — |
| Brian Westphal | Samsara | Speaker | Ray Serve for IOT @ Samsara | — |
| Cade Daniels | Anyscale | Speaker | Enabling Cost-Efficient LLM Serving with Ray Serve | — |
| Carlos Costa | IBM | Speaker | Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift AI | — |
| Chaoyu Yang | BentoML | Speaker | BentoML or RayServe, You Can Choose Both with BentoRay | — |
| Charles Fan | MemVerge | Speaker | Gismo for Ray: A Multi-Node Shared Memory Object Store That Accelerates Ray Workloads | — |
| Cheng Su | Anyscale | Speaker | How Anyscale Speeds up ML Data Processing with Ray | — |
| Chia-Wei Chen | Speaker | Last Mile Data Processing for ML Training using Ray | — | |
| Chongxiao Cao | Uber | Speaker | Enabling End-to-End LLMOps on Michelangelo with Ray | — |
| Chris Van Dyke | Cloudera | Speaker | Making it easy to provision Ray clusters to support enterprise AI/ML efforts | — |
| Chris Van Pelt | Weights & Biases | Speaker | Understanding the Landscape of the Latest Large Models | — |
| Chris Wolf | VMware | Speaker | Standing Up Ray Clusters in the Blink of an AI to Drive Private AI | — |
| Cindy Zhang | Anyscale | Speaker | Deploying Many Models Efficiently with Ray Serve | — |
| David Scott | Instacart | Speaker | Scaling Computer Vision Models with Ray: A Cost-Effective and Efficient Distributed Training Framework | — |
| David Xia | Spotify | Speaker | How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience | — |
| Dhaval Shah | DoorDash | Speaker | From Good to Great: Elevating DoorDash Model Training with Ray | — |
| Dinesh Ramasamy | Verse Innovation | Speaker | Large language-style universal models for Short Video recommendations | — |
| Edward Oakes | Anyscale | Speaker | Building Production AI Applications with Ray Serve | — |
| Eric Liang | Anyscale | Speaker | Ray Data Streaming for Large-Scale ML Training and Inference | — |
| Frank Gu | Speaker | Hyperparameter Tuning with Ray[Tune] for Next-Gen training platform at LinkedIn | — | |
| Frank Luan | UC Berkeley | Speaker | The Ray Dataplane: History and the Cloudsort World Record | — |
| Goku Mohandas | Anyscale | Speaker | Lessons from Running RAG Applications in Production | — |
| Han Li | Instacart | Speaker | Build Instacart Training Platform on Ray | — |
| Hao Chen | Anyscale | Speaker | How Anyscale Speeds up ML Data Processing with Ray | — |
| Harish Sitaraman | Amazon Web Services | Speaker | Building an Instant-On Serverless Platform for Large-Scale Data Processing Using Ray | — |
| Harrison Chase | LangChain | Speaker | Evaluating and Managing LLM Applications with the Langsmith Project | — |
| Harshit Singh | LexisNexis | Speaker | Efficient Expert Witness Profiling with Ray: Automated Key Phrase Extraction from Legal Documents | — |
| Janez Ales | BASF | Speaker | Ray-based Horizontally Scalable In-Memory Graph Platform at BASF | — |
| Japson Jeyasekaran | Amazon Web Services | Speaker | Building an Instant-On Serverless Platform for Large-Scale Data Processing Using Ray | — |
| Jasper van Heugten | minds.ai | Speaker | Semiconductor Fab Production Scheduling Using Deep Reinforcement Learning | — |
| Jerry Liu | LlamaIndex | Speaker | Practical Data Considerations for Building Production-Ready LLM Applications | — |
| Jiajun Yao | Anyscale | Speaker | Redesigning Scheduling in Ray to Improve Cost-Efficiency at Scale | — |
| Jim Busche | IBM | Speaker | Parallel inferencing with KServe Ray integration | — |
| Joey Asperger | Kevala | Speaker | Ray for Large-Scale, Time-Series Energy Forecasting to Plan a More Resilient Power Grid | — |
| John Allard | OpenAI | Speaker | How Snorkel Builds Interactive Enterprise ML Products Using Ray | — |
| Jon Park | Clari | Speaker | Deploying Many Models Efficiently with Ray Serve | — |
| Joseph Spisak | Meta | Speaker | Llama, Scaling Up LLMs in an Open Ecosystem | — |
| Josh Bauer | Sematic | Speaker | On-Demand Ray Clusters in ML Workflows via KubeRay & Sematic | — |
| Josh Poduska | Domino Data Lab | Speaker | Bridging MLOps and LLMOps: Integrating Governed Generative AI into your Enterprise | — |
| Joshua Albert | Touch Medical Intelligence Inc | Speaker | Scaling AI Health Assistants: Challenges and Solutions | — |
| Justin Olsson | Anyscale | Speaker | Legal Questions Around LLMs and Generative AI | — |
| Justin Yu | Anyscale | Speaker | Fault Tolerant Training of Large Models: Examples and Tutorial | — |
| Kai Wang | NetEase | Speaker | Ray/RLLib-Empowered Reinforcement Learning based Recommender Systems in NetEase Game | — |
| Kai-Hsun Chen | Anyscale | Speaker | KubeRay: A Ray cluster management solution on Kubernetes | — |
| Keshi Dai | Spotify | Speaker | How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience | — |
| Kornel Csernai | DoorDash | Speaker | Modernizing DoorDash Model Serving Platform with Ray Serve | — |
| Kourosh Hakhamaneshi | Anyscale | Speaker | Lessons From Fine-Tuning Llama-2 | — |
| Lingyi Liu | Netflix | Speaker | Heterogeneous Training Cluster with Ray at Netflix | — |
| Luyang Wang | Verizon | Speaker | Large Scale Pathways Recommender Systems (PaRS) at Verizon | — |
| M Waleed Kadous | Anyscale | Speaker | The New Self-Hosted LLM Tech Stack: Ray, HuggingFace + LangChain | — |
| Mario Bourgoin | Amazon Web Services | Speaker | A Crash Course on LLMOps for Foundational Model Fine Tuning: Challenges & Alternatives on AWS | — |
| Matej Tomazin | Antbit.io | Speaker | Decentralized Ray - Scaling Ray for Global Inference | — |
| Max Mergenthaler | Nixtla | Speaker | TimeGPT: A Foundation Large Time Series Model | — |
| Michael Maximilien | IBM | Speaker | Ray, Knative, and Running Serverless Workloads in the Cloud | — |
| Mingyuan Tian | Speaker | Hyperparameter Tuning with Ray[Tune] for Next-Gen training platform at LinkedIn | — | |
| Mohammad Oloomi | Wesfarmers OneDigital | Speaker | OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale | — |
| Mustafa Eyceoz | Red Hat | Speaker | How to simplify execution of cloud-native model training and validation with CodeFlare: A Hands-On Demo | — |
| Nick Hill | IBM | Speaker | Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift AI | — |
| Pablo Delgado | Netflix | Speaker | Heterogeneous Training Cluster with Ray at Netflix | — |
| Pang Wu | Samsara | Speaker | Building Samara’s Machine Learning Platform with Ray | — |
| Paridhi Jha | Wesfarmers OneDigital | Speaker | OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale | — |
| Patrick Ames | Amazon Web Services | Speaker | From Spark to Ray: An Exabyte-Scale Production Migration Case Study | — |
| Patrick Dolan | FlightAware | Speaker | FlightAware and Ray: Scaling Distributed XGBoost and Parallel Data Ingestion | — |
| Paul Schweigert | IBM | Speaker | Ray, Knative, and Running Serverless Workloads in the Cloud | — |
| Peter Haddad | Lockheed Martin | Speaker | AI Factory Accelerating Solutions with Ray | — |
| Peyman Tavallali | JPMorgan Chase | Speaker | Scaling time-series forecasting models to cope with the multi-verse with Ray | — |
| Philipp Moritz | Anyscale | Speaker | Lessons from Running RAG Applications in Production | — |
| Qi Zhou | Niantic | Speaker | Build Augmented Reality Maps With Ray | — |
| Quingxian Lai | Speaker | Last Mile Data Processing for ML Training using Ray | — | |
| Rajpal Paryani | Instacart | Speaker | Build Instacart Training Platform on Ray | — |
| Raymond Lee | Speaker | Last Mile Data Processing for ML Training using Ray | — | |
| Richard Liu | Speaker | Serving Large Language Models with KubeRay on TPUs | — | |
| Ricky Xu | Anyscale | Speaker | Ray Observability 2.0: How to Debug Your Ray Applications with New Observability Tooling | — |
| Ritwik Bera | Zoox | Speaker | Supercharging self-driving algorithms development with Ray: scaling simulation workloads and democratizing autotuning at Zoox | — |
| Runze Wu | NetEase | Speaker | Ray/RLLib-Empowered Reinforcement Learning based Recommender Systems in NetEase Game | — |
| Ruoyu Huang | Instabase | Speaker | Deploying Ray Cluster on an Air-Gapped Kubernetes Cluster with Tight Security Control: Challenges and Best Practices | — |
| SangBin Cho | Anyscale | Speaker | Ray Observability 2.0: How to Debug Your Ray Applications with New Observability Tooling | — |
| Sasha Ovsankin | Speaker | Inference Graphs at Linkedin Using Ray-Serve | — | |
| Saurabh Tripathi | Samsara | Speaker | Building Samara’s Machine Learning Platform with Ray | — |
| Sean Sheng | BentoML | Speaker | BentoML or RayServe, You Can Choose Both with BentoRay | — |
| Shaowei Su | Airbnb | Speaker | Optimizing LLM Training with Airbnb's Next-Gen ML Platform | — |
| Sharan Srinivasan | Samsara | Speaker | Building Samara’s Machine Learning Platform with Ray | — |
| Shreyas Krishnaswamy | Anyscale | Speaker | Building Production AI Applications with Ray Serve | — |
| Siddharth Kodwani | DoorDash | Speaker | Modernizing DoorDash Model Serving Platform with Ray Serve | — |
| Sihan Wang | Anyscale | Speaker | Deploying Many Models Efficiently with Ray Serve | — |
| Sofian Hnaide | Anyscale | Speaker | Anyscale Workspaces: A Scalable Interactive ML Development Environment with Zero Setup | — |
| Sriram Sankar | Anyscale | Speaker | Train and Deploy LLM/Generative AI Application Cheaper, Faster and Safer with Anyscale’s Infrastructure | — |
| Stephanie Wang | Anyscale | Speaker | The Ray Dataplane: History and the Cloudsort World Record | — |
| Sven Mika | Anyscale | Speaker | DeepMind’s DreamerV3 on RLlib with multiple GPUs: Out-of-the-box, fast model-based RL. | — |
| Swaroop Chitlur | DoorDash | Speaker | From Good to Great: Elevating DoorDash Model Training with Ray | — |
| Taneem Ibrahim | Red Hat | Speaker | Simplified Training, Tuning and Deployment of Foundational Models as a Service with Red Hat OpenShift AI | — |
| Tanmay Chordia | Anyscale | Speaker | Enabling Cost-Efficient LLM Serving with Ray Serve | — |
| Ted Chang | IBM | Speaker | Parallel inferencing with KServe Ray integration | — |
| Tengwei Cai | Ant Group | Speaker | How Ray Empowered Ant Group to Deliver a Large-Scale Online Serverless Platform | — |
| Tony Wang | Stanford University | Speaker | Building a distributed query engine with Ray | — |
| Travis Addair | Predibase Inc | Speaker | 50x Faster Fine-Tuning in 10 Lines of YAML with Ludwig and Ray | — |
| Tristan Zajonc | Continual | Speaker | How to Build an AI Copilot for Your Application | — |
| Vedant Jain | Amazon Web Services | Speaker | A Crash Course on LLMOps for Foundational Model Fine Tuning: Challenges & Alternatives on AWS | — |
| Vedant Jain | Amazon Web Services | Speaker | Enterprise Vector-based Information Retrieval & Prompt Engineering at Scale using Open Source on AWS | — |
| Wei-Yu Yen | Speaker | Hyperparameter Tuning with Ray[Tune] for Next-Gen training platform at LinkedIn | — | |
| Weichen Xu | Databricks | Speaker | Ray on Spark | — |
| Will Hang | Snorkel AI | Speaker | How Snorkel Builds Interactive Enterprise ML Products Using Ray | — |
| Winston Chiang | Speaker | Serving Large Language Models with KubeRay on TPUs | — | |
| Xuning (Mike) Tang | Verizon | Speaker | Large Scale Pathways Recommender Systems (PaRS) at Verizon | — |
| Yi Chang | Anyscale | Speaker | Ray Scalability Deep Dive: The Journey to Support 4,000 Nodes | — |
| Yifei Feng | Anyscale | Speaker | Train and Deploy LLM/Generative AI Application Cheaper, Faster and Safer with Anyscale’s Infrastructure | — |
| Yiqing Wang | Instabase | Speaker | Deploying Ray Cluster on an Air-Gapped Kubernetes Cluster with Tight Security Control: Challenges and Best Practices | — |
| Yuan-Chi Chang | IBM | Speaker | Automatically scaling the execution of Foundation Models workflows: Ray with CodeFlare and Red Hat OpenShift Data Science Pipelines | — |
| Yunpeng Pan | Zoox | Speaker | Supercharging self-driving algorithms development with Ray: scaling simulation workloads and democratizing autotuning at Zoox | — |
| Yunxuan Xiao | Anyscale | Speaker | Ray Train: A Library for Seamless and Production-Ready Distributed Deep Learning | — |
| Zachary Carrico | Freenome | Speaker | A Ray-based ML Platform for Early Cancer Detection | — |
| Zongheng Yang | UC Berkeley | Speaker | SkyPilot: Run AI on Any Cloud | — |
Sources
- https://web.archive.org/web/20230914000259/https://raysummit.anyscale.com/
- https://web.archive.org/web/20230906183941/https://raysummit.anyscale.com/agenda
- https://web.archive.org/web/20231003233005/https://www.anyscale.com/events/2023/09/18/ray-summit-2023
- https://raysummit23.anyscale.com/venue
- https://raysummit23.anyscale.com/sponsors
- https://anyscale.com/blog/ray-summit-2023-call-for-proposals-is-now-open