Anyscale

Founded in 2019. Privately Held.

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Large language model (LLM) infrastructure.

Blog posts published by month since the start of

252 total blog posts published.

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Blog content

post title author published words HN
Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Models to Unique Applications Kourosh Hakhamaneshi, Rehaan Ahmad Aug. 11, 2023 5637 308
How Ray and Anyscale Make it Easy to Do Massive-Scale Machine Learning on Aerial Imagery Richard Decal Nov. 08, 2022 1563 -
Wildlife Studios Serves In-game Offers 3X Faster at 1/10th the Cost with Ray Serve Tricia Fu Nov. 08, 2022 1064 -
Announcing Ray 2.0 Anyscale Ray Team Aug. 23, 2022 705 -
Building Highly Available and Scalable Online Applications on Ray at Ant Group Tengwei Cai, Yang Liu, Chengxi Luo Sep. 08, 2021 2322 1
Four Reasons Why Leading Companies Are Betting On Ray Zhe Zhang, Ion Stoica, Ben Lorica Oct. 19, 2022 1580 -
How Anastasia accelerated their ML processes 9x with Ray and Anyscale Juan Roberto Honorato Aug. 31, 2021 1290 -
Here’s what you need to look for in a model server to build ML-powered services Ben Lorica, Ion Stoica Aug. 07, 2020 1373 -
Online Resource Allocation with Ray at Ant Group Xingyu Lu, Yang Liu, Tengwei Cai, Fengbin Fang Mar. 30, 2021 1838 1
Five Key Features for a Machine Learning Platform Ben Lorica, Ion Stoica Jul. 13, 2020 1517 -
Why you should build your AI Applications with Ray Ben Lorica, Ion Stoica May. 04, 2021 1375 -
Autoscaling clusters with Ray Ameer Haj Ali, Javier Redondo May. 17, 2021 2325 -
Understanding the Ray Ecosystem and Community Ben Lorica, Ion Stoica Apr. 23, 2020 980 -
The Ideal Foundation for a General Purpose Serverless Platform Ben Lorica, Eric Liang, Ion Stoica Nov. 05, 2020 1451 2
The Future of Computing is Distributed Ion Stoica Feb. 26, 2020 1157 -
Anyscale Unveils Ray 2.0 and Anyscale Innovations at Ray Summit 2022; Adds an Additional $99M Funding from Existing Investors Addition, Intel Capital, and Foundation Capital - Aug. 23, 2022 827 -
Ray Summit, the Industry Event for Scalable AI, Unveils New Innovations in Ray and the Anyscale Platform; Features Speakers from Uber, IBM, OpenAI, Shopify, Dow and Numerous Global Organizations - Aug. 24, 2022 557 -
Machine Learning for Developers Goku Mohandas Jul. 26, 2023 688 -
Processing 2 Billion Images for Stable Diffusion Model Training - Definitive Guides with Ray Series Max Pumperla, Marwan Sarieddine May. 14, 2024 4209 -
Presentations from the Jan 30, 2020 Ray Meetup in San Francisco Dean Wampler Feb. 04, 2020 156 -
Introducing Anyscale: The Future Is Distributed Robert Nishihara Dec. 07, 2021 702 1
Best Machine Learning Talks from Ray Summit 2021 Michael Galarnyk Jul. 20, 2021 746 -
Ray Summit 2022 stories - ML Platforms Anyscale Ray Team Mar. 03, 2023 628 -
How to Speed Up Pandas with Modin Michael Galarnyk Mar. 03, 2021 1041 -
Ray Forward 2022 Zhe Zhang Aug. 18, 2022 1855 -
Introducing Collective Communication Primitive APIs in Ray Hao Zhang, Richard Liaw May. 28, 2021 1494 -
Running and Monitoring Distributed ML with Ray and whylogs Anthony Naddeo, Danny Leybzon Nov. 22, 2021 1523 -
How Nixtla uses Ray to accurately predict more than a million time series in half an hour Nixtla Team Jun. 13, 2022 1152 -
Ray 1.13: Improving support for shuffling terabyte-scale and larger datasets Stephanie Wang, Jiao Dong, Dmitri Gekhtman, Sang Cho Jun. 09, 2022 680 -
LiveEO supercharges their ML infrastructure and accelerates their geospatial workloads practice Toby Rahloff, Phi Nguyen, Alex Streed Apr. 14, 2023 658 -
Serverless Kafka Stream Processing with Ray Javier Redondo Jul. 13, 2021 3413 -
Reinforcement learning sessions at Ray Summit: A guided tour Avnish Narayan, Christy Bergman, Jun Gong Jun. 23, 2022 874 -
Building an end-to-end ML pipeline using Mars and XGBoost on Ray Chaokun Yang, Yiming Yu Jan. 05, 2022 2161 -
Anyscale Endpoints: Embedding endpoint, Llama-2 70B fine-tuning and improved sign-up experience Anyscale team Nov. 30, 2023 376 -
The 2021 Ray Community Pulse Survey is Now Open Michael Galarnyk May. 12, 2021 432 -
Fine-Tuning LLMs: LoRA or Full-Parameter? An in-depth Analysis with Llama 2 Artur Niederfahrenhorst, Kourosh Hakhamaneshi, Rehaan Ahmad Sep. 06, 2023 3597 22
Announcing Ray 2.3: performance improvements, new features and new platforms Richard Liaw, Cade Daniel, Jules S. Damji, Zhe Zhang Feb. 24, 2023 1329 -
Why I joined Anyscale Jaikumar Ganesh Nov. 29, 2021 791 -
Fast AutoML with FLAML + Ray Tune Qingyun Wu, Chi Wang, Antoni Baum, Richard Liaw, Michael Galarnyk Aug. 24, 2021 1802 -
Building a Self Hosted Question Answering Service using LangChain + Ray in 20 minutes Waleed Kadous May. 08, 2023 1693 -
Ray 1.12: Ray AI Runtime (alpha), usage data collection, and more Paige Bailey, Richard Liaw, Jian Xiao, Chandler Gibbons Apr. 14, 2022 570 -
Hyperparameter Search with Hugging Face Transformers Richard Liaw Nov. 03, 2020 595 -
How to Speed Up XGBoost Model Training Michael Galarnyk Dec. 15, 2021 1068 -
Siemens brings reinforcement learning to energy, transportation and logistics Erik Martinez May. 03, 2022 334 -
How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience Anyscale Ray Team Nov. 09, 2023 1259 -
How continuous batching enables 23x throughput in LLM inference while reducing p50 latency Cade Daniel, Chen Shen, Eric Liang, Richard Liaw Jun. 22, 2023 3568 110
Building an LLM open source search engine in 100 lines using LangChain and Ray Waleed Kadous Apr. 18, 2023 1780 3
What is hyperparameter tuning? Juan Navas Feb. 08, 2022 1832 -
10 must-attend Ray Summit sessions: Generative AI, scalable ML workloads, and more Jules S. Damji, Ben Lorica May. 10, 2023 1078 -
Improve Utilization and Simplify Cluster Management with Anyscale Job Queues Dominic Catalano, Alexey Kudinkin Jul. 23, 2024 735 -
Ray Summit 2021 CFP Now Open! Zhe Zhang, Ben Lorica Jan. 13, 2021 230 -
Ray 1.11: Redisless Ray, a docs redesign, and Python 3.9 support Mingwei Tian, Chandler Gibbons Mar. 09, 2022 701 1
Ray Summit 2024 Call for Proposals is now open Anyscale team Apr. 19, 2024 264 -
Deploying XGBoost models with Ray Serve Simon Mo, Chandler Gibbons Mar. 02, 2022 1524 -
Anyscale and Meta Collaborate to Advance the Llama-2 Ecosystem Robert Nishihara, Joe Spisak Sep. 07, 2023 325 -
Open Source LLMs: Viable for Production or a Low-Quality Toy? Anyscale Ray Team Nov. 20, 2023 855 -
The Infinite Laptop Ion Stoica, Robert Nishihara Oct. 08, 2020 945 -
New in KubeRay 0.2.0: Autoscaling (alpha), simplified installation, and more Jiaxin Shan, KubeRay Team Apr. 19, 2022 524 -
How ByteDance Scales Offline Inference with multi-modal LLMs to 200 TB Data Amog Kamsetty, Hao Chen, Liguang Xie Aug. 14, 2023 1872 7
Ray 2.5 features training and serving for LLMs, Multi-GPU training in RLlib, and enhanced Ray Data support Richard Liaw, Jules S. Damji Jun. 13, 2023 1681 -
Llama, Scaling Up LLMs in an Open Ecosystem Anyscale Ray Team Oct. 16, 2023 1246 -
Build and Scale a Powerful Query Engine with LlamaIndex and Ray Jerry Liu, Amog Kamsetty Jun. 26, 2023 2524 -
Introducing Distributed XGBoost Training with Ray Kai Fricke, Richard Liaw, Amog Kamsetty Jun. 16, 2021 1994 -
Deploy Ray Serve with up to 50% fewer nodes using Anyscale Replica Compaction Matt Connor, Akshay Malik, Cindy Zhang Jul. 15, 2024 883 -
Training 175B Parameter Language Models at 1000 GPU scale with Alpa and Ray Jiao Dong, Hao Zhang, Lianmin Zheng, Jun Gong, Jules S. Damji, Phi Nguyen Mar. 22, 2023 2713 -
Heterogeneous Training Cluster with Ray at Netflix Anyscale Ray Team Oct. 20, 2023 902 -
Reinforcement Learning with RLlib in the Unity Game Engine Sven Mika Jan. 19, 2021 2133 -
Advances in Foundation Models — Technology, Society, and Applications Anyscale Ray Team Nov. 03, 2023 1460 -
Ray 2.6 features streaming for Serve and Train and new Multi-GPU Learner API Jules S. Damji, Richard Liaw Jul. 25, 2023 1426 -
Reinforcement learning with Deep Q Networks Misha Laskin Mar. 01, 2022 1189 -
Announcing Ray Summit, May 27-28, 2020 Dean Wampler, Ben Lorica Jan. 10, 2020 362 -
Comparing LLM performance: Introducing the Open Source Leaderboard for LLM APIs Anyscale team Dec. 21, 2023 1202 2
Time Series Forecasting using an LSTM version of RNN with PyTorch Forecasting and Torch Lightning Christy Bergman, Amog Kamsetty Dec. 21, 2021 2157 -
Ray Serve: Tackling the cost and complexity of serving AI in production Akshay Malik, Edward Oakes, Phi Nguyen Sep. 25, 2023 2392 -
We Pre-Trained Stable Diffusion Models on 2 billion Images and Didn't Break the Bank - Definitive Guides with Ray Series Max Pumperla, Marwan Sarieddine May. 21, 2024 4553 -
Reinforcement learning based on market simulation at JPMorgan Erik Martinez May. 03, 2022 287 -
Ray 1.10: Windows support beta, enhanced job submission, and more Chandler Gibbons Feb. 07, 2022 447 2
Now Available: The LLM Router Template Amjad Almahairi Jul. 19, 2024 256 -
Biolexis Boosts Their New AI/ML Drug Discovery Platform Using Anyscale’s Fully-Managed Ray Platform Jake Carter, Phi Nguyen Nov. 09, 2022 622 -
Simplify your ML Development Cycle with Anyscale and Weights & Biases Phi Nguyen Jan. 31, 2023 715 -
Why I Joined Anyscale: Solving Cutting-Edge Problems in a Time of Enormous Change Sidney Rabsatt Apr. 19, 2023 260 -
Videos and Slides for the Fourth Ray Summit Connect, August 12, 2020 Dean Wampler Aug. 12, 2020 124 -
Scaling up PyTorch Lightning hyperparameter tuning with Ray Tune Kai Fricke Aug. 18, 2020 973 -
Announcing Ray 2.4.0: Infrastructure for LLM training, tuning, inference, and serving Richard Liaw, Jules S. Damji, Jiajun Yao Apr. 27, 2023 1692 -
Smart supply chain management with reinforcement learning at Dow Erik Martinez May. 03, 2022 329 -
Anyscale Endpoints Preview: Fast, Cost-Efficient, and Scalable LLM APIs Ameer Haj Ali, Robin Singh Aug. 03, 2023 363 -
Fine-tuning LLMs for longer context and better RAG systems Artur Niederfahrenhorst, Kourosh Hakhamaneshi Feb. 13, 2024 2847 1
Building Production AI Applications with Ray Serve Anyscale Ray Team Oct. 24, 2023 1213 -
Ray version 1.9 has been released Michael Galarnyk Dec. 06, 2021 395 -
How ThirdAI uses Ray for Parallel Training of Billion-Parameter Neural Networks on Commodity CPUs Vihan Lakshman, Pratik Pranav, Siddharth Jain, Tharun Medini Aug. 29, 2023 1643 78
Introducing Ray Lightning: Multi-node PyTorch Lightning training made easy Amog Kamsetty, Richard Liaw, Will Drevo Aug. 19, 2021 1851 9
Ray 2.7 features major stability improvements to Ray AI Libraries and KubeRay and introduces RayLLM Jules S. Damji, Richard Liaw Sep. 18, 2023 1798 -
Large-scale distributed training with TorchX and Ray Mark Saroufim, Jules S. Damji Mar. 24, 2022 1385 -
Ray version 1.8 has been released Michael Galarnyk Nov. 04, 2021 527 -
Optimizing LLM Training with Airbnb's Next-Gen ML Platform Anyscale Ray Team Oct. 30, 2023 1048 -
Data Processing Support in Ray Sang Cho, Alex Wu, Clark Zinzow, Eric Liang, Stephanie Wang Feb. 16, 2021 1178 2
Video and Code for Anyscale Academy, Ray Crash Course, May 27, 2020 Dean Wampler May. 28, 2020 75 -
Accelerating AI: Harnessing Intel(R) Gaudi(R) 3 with Ray 2.10 Ramit Hora Apr. 09, 2024 596 -
Attention Nets and More with RLlib's Trajectory View API Sven Mika Apr. 21, 2021 1475 -
Distributed deep learning with Ray Train is now in Beta Matthew Deng, Amog Kamsetty, Richard Liaw, Will Drevo Jan. 25, 2022 2105 -
Serving PyTorch models with FastAPI and Ray Serve Simon Mo, Chandler Gibbons Feb. 23, 2022 1506 2
Ray Serve + FastAPI: The best of both worlds Phi Nguyen Aug. 02, 2022 1229 -
Serving ML Models in Production: Common Patterns Simon Mo, Edward Oakes, Michael Galarnyk Oct. 01, 2021 2759 -
Introducing Anyscale’s Unified Log Viewer Alan Guo, Gene Su Jul. 18, 2024 405 -
Cross-modal Search for E-commerce: Building and Scaling a Cross-Modal Image Retrieval App Marwan Sarieddine, Natalia Czerep, Mateusz Kwasniak, Artur Zygadło Jun. 04, 2024 3253 -
Ray breaks the $1/TB barrier as the world’s most cost-efficient sorting system Frank Sifei Luan, UC Berkeley Jan. 25, 2023 1257 36
Modern Distributed C++ with Ray Guyang Song, Yu Qi Nov. 11, 2021 2651 -
The Emergence of Multi-cloud Native Applications and Platforms Ben Lorica, Ion Stoica Jan. 05, 2021 1463 -
Adtriba Accelerates and Advances Media Mix Modeling Using the Anyscale Fully-Managed Ray Platform Houssem Eddine Gharbi, Tim Kreienkamp, Phi Nguyen Nov. 08, 2022 957 -
​​Reinventing Multi-Modal Search with Anyscale and MongoDB Marwan Sarieddine, Kamil Kaczmarek Jul. 25, 2024 5145 -
How to tune hyperparameters on XGBoost Juan Navas, Richard Liaw Feb. 09, 2022 1305 -
Infusing AI and ML into integrated circuit design for faster chip delivery, better chip performance IBM Research Team Jun. 16, 2022 1390 -
Parallelizing Python Code Dawid Borycki, Michael Galarnyk Sep. 02, 2021 1668 2
Retrieval Augmented Generation with Huggingface Transformers and Ray Amog Kamsetty Feb. 10, 2021 1050 -
Practical Data Considerations for Building Production-Ready LLM Applications Anyscale Ray Team Oct. 19, 2023 1116 -
Llama 2 is about as factually accurate as GPT-4 for summaries and is 30X cheaper Waleed Kadous Aug. 23, 2023 2933 143
New on Anyscale: Debug and Optimize Ray Applications Faster with Structured Logging Jiajun Yao, Kai-Hsun Chen Jul. 16, 2024 449 -
Ray Datasets for large-scale machine learning ingest and scoring Clark Zinzow, Alex Wu, Jiajun Yao, Eric Liang, Chen Shen Feb. 14, 2022 1661 2
How to Speed up Scikit-Learn Model Training Michael Galarnyk Feb. 03, 2021 911 -
Ray + Arize, Productionize ML for Scale and Usability Dat Ngo Aug. 22, 2022 1828 -
Gang Scheduling Ray Clusters on Kubernetes with Multi-Cluster-App-Dispatcher (MCAD) Abhishek Malvankar (IBM Research) and Dmitri Gekhtman (Anyscale) Nov. 16, 2022 1406 1
Flexible, cross-language, distributed model inference framework: Ray Serve with Java API Tengwei Cai, Yang Liu, Chengxi Luo, Xiaofeng Yang, Simon Mo Dec. 13, 2022 910 -
Ray Distributed Library Patterns Eric Liang, Zhe Zhang Jun. 14, 2021 1391 -
Biggest takeaways from our RL tutorial: Long-term rewards, offline RL, and more Christy Bergman Apr. 06, 2022 1114 -
Easily Debug Ray Applications with Ray Distributed Debugger Anyscale team May. 15, 2024 624 -
Inference Graphs at LinkedIn Using Ray-Serve Anyscale Ray Team Nov. 09, 2023 1267 -
End-to-end LLM Workflows Guide Goku Mohandas Jun. 17, 2024 4910 1
Building Context-Aware Reasoning Applications with LangChain and LangSmith Anyscale Ray Team Oct. 18, 2023 1214 -
Writing your First Distributed Python Application with Ray Michael Galarnyk Aug. 12, 2021 2237 -
Ray 2.2: Improved developer experience, performance and stability Richard Liaw Jan. 23, 2023 789 -
Building an LLM-powered GitHub bot to improve your pull requests Max Pumperla Nov. 15, 2023 3491 -
Videos and Slides for the Second Ray Summit Connect, June 17, 2020 Sophia DeMartini, Dean Wampler Jun. 18, 2020 128 -
Configuring and Scaling ML with Hydra + Ray Richard Liaw, Bill Chambers, Jieru Hu Jan. 26, 2021 480 -
How Hutom.io uses Ray and PyTorch to Scale Surgical Video Analysis and Review Jihun Yoon Oct. 26, 2021 1575 -
Ray version 1.6 is released Asawari Samant Aug. 23, 2021 799 -
Introducing RLlib Multi-GPU Stack for Cost Efficient, Scalable, Multi-GPU RL Agents Training Avnish Narayan, Kourosh Hakhamaneshi Jun. 26, 2023 1058 -
Building an LLM Router for High-Quality and Cost-Effective Responses Amjad Almahairi Jul. 01, 2024 4430 1
Anyscale Announces $40M in Series B Funding Led by NEA Robert Nishihara Oct. 21, 2020 629 -
An informal introduction to reinforcement learning Misha Laskin Feb. 22, 2022 1187 3
Practical tips for training Deep Q Networks Misha Laskin Mar. 03, 2022 875 -
Don’t Miss: Hands-On Ray Training at Ray Summit 2024 Kamil Kaczmarek Aug. 13, 2024 788 -
7 must-attend Ray Summit sessions: RL-powered traffic control, infra-less ML, and more Jules S. Damji, Ben Lorica Jun. 01, 2022 653 -
Low-latency Generative AI Model Serving with Ray, NVIDIA Triton Inference Server, and NVIDIA TensorRT-LLM Neelay Shah, Akshay Malik Mar. 13, 2024 642 -
What is distributed training? Keith Pijanowski, Michael Galarnyk Apr. 26, 2022 727 -
Considerations for Deploying Machine Learning Models in Production Jules S. Damji, Michael Galarnyk Nov. 16, 2021 1791 -
Many Models Batch Training at Scale with Ray Core Jules S. Damji, Antoni Baum Jan. 19, 2023 2178 -
Monitoring and Debugging Ray workloads: Ray Metrics SangBin Cho, Alan Guo, Ricky Xu, Eric Liang Nov. 08, 2022 1221 -
Fine tuning is for form, not facts Waleed Kadous, Kourosh Hakhamaneshi Jul. 05, 2023 1631 -
Introducing the Anyscale Snowflake Connector Eric Greene Jul. 20, 2023 745 -
Reducing the Cost of Pre-training Stable Diffusion by 3.7x with Anyscale Yunxuan Xiao, Hao Chen May. 09, 2024 2176 5
Considerations for deploying machine learning models in production: Part 2 Jules S. Damji Feb. 04, 2022 2475 -
Cost Effective Machine Learning with Ray Miha Jenko Dec. 20, 2021 869 -
Ray version 1.7 has been released Michael Galarnyk Oct. 11, 2021 722 -
Riot Games and deep reinforcement learning in gaming Erik Martinez May. 03, 2022 364 -
Why I joined Anyscale: The vision, the tech, and the team Sriram Sankar Feb. 02, 2022 648 -
How Ray solves common production challenges for generative AI infrastructure Antoni Baum, Eric Liang, Jun Gong, Kai Fricke, Richard Liaw Mar. 20, 2023 1494 -
5 reasons to attend this month’s Production RL Summit Chandler Gibbons Mar. 22, 2022 669 -
Streaming distributed execution across CPUs and GPUs Eric Liang, Stephanie Wang, Cheng Su May. 11, 2023 2067 -
From Ray to Chronos: Build end-to-end AI use cases using BigDL on top of Ray Wesley Du, Junwei Deng, Kai Huang, Shan Yu, Shane Huang Nov. 02, 2021 1594 -
Redis in Ray: Past and future Mingwei Tian Mar. 15, 2022 930 1
Multi-model composition with Ray Serve deployment graphs Jiao Dong, Shreyas Krishnaswamy, Simon Mo, Edward Oakes May. 18, 2022 2554 -
The reinforcement learning framework Misha Laskin Feb. 24, 2022 921 -
An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab Michael Galarnyk, Sven Mika Aug. 26, 2021 2649 -
Ray Summit Series - Scaling Parallel Python Jobs Anyscale Ray Team Mar. 16, 2023 599 -
Foobot optimizes building energy efficiency by training fully autonomous control agents for HVAC systems, bringing energy savings to office buildings, hospitals, schools and commercial buildings. Antoine Galataud, Phi Nguyen, Inouk Bourgon, Adrien Lafond Dec. 19, 2022 751 -
Videos and Slides for the First Ray Summit Connect, May 13, 2020 Dean Wampler May. 15, 2020 137 -
Leveraging the Possibilities of Ray Serve in Implementing a Scalable, Fully Automated Digital Verification Service Tanja Bayer Nov. 09, 2021 1324 -
Forecasting at Scale Phi Nguyen, Max Mergenthaler Feb. 02, 2023 683 -
Introducing the Anyscale Databricks Connector Eric Greene Jun. 15, 2023 632 -
Ray Summit 2023 Call for Proposals is now open Jules S. Damji Jan. 12, 2023 777 -
Fast, flexible, and scalable data loading for ML training with Ray Data Stephanie Wang, Scott Lee, Cheng Su, Hao Chen, Eric Liang Sep. 15, 2023 3238 4
Executing a distributed shuffle without a MapReduce system Stephanie Wang Mar. 22, 2021 1675 -
Life @ Anyscale: Investing in our communities Tyler Faust May. 26, 2022 271 -
Anyscale and Lambda - Addressing AI Scarcity with Engineering Anyscale team Nov. 21, 2023 585 -
Forbes AI 50: America’s Most Promising Artificial Intelligence Companies Sophia DeMartini Jul. 16, 2020 53 -
RAG at Scale: 10x Cheaper Embedding Computations with Anyscale and Pinecone Scott Lee, Kyle Huang, Cheng Su, Hao Chen Jan. 16, 2024 995 1
Ray 2.8 features Ray Data extensions, AWS Neuron cores support, and Dashboard improvements Jules S. Damji, Richard Liaw Nov. 07, 2023 791 -
The Third Generation of Production ML Architectures Waleed Kadous Sep. 15, 2021 2388 3
Scaling Time Series Forecasting on Ray: ARIMA and Prophet on Ray Christy Bergman Nov. 23, 2021 2725 -
Analyzing memory management and performance in Dask-on-Ray Stephanie Wang Jun. 29, 2021 2784 1
Sailing to victory with reinforcement learning Erik Martinez Feb. 28, 2022 449 -
Update on Ray CVE-2023-48022: New Verification Tooling Available Anyscale team Mar. 27, 2024 606 -
Update on Ray CVEs CVE-2023-6019, CVE-2023-6020, CVE-2023-6021, CVE-2023-48022, CVE-2023-48023 Anyscale team Nov. 30, 2023 508 -
Simplify your MLOps with Ray & Ray Serve Phi Nguyen Jul. 26, 2022 1167 -
Video and Code for Anyscale Academy, Reinforcement Learning with Ray RLlib, June 24, 2020 Dean Wampler Jun. 25, 2020 69 -
Ray Spotlight Series: Multitenant Serve Applications with Runtime Envs as Containers Sam Chan, Cindy Zhang Jun. 13, 2024 800 -
How to fine tune and serve LLMs simply, quickly and cost effectively using Ray + DeepSpeed + HuggingFace Waleed Kadous, Jun Gong, Antoni Baum, Richard Liaw Apr. 10, 2023 2055 -
Turbocharge LangChain: guide to 20x faster embedding Amog Kamsetty, Philipp Moritz May. 03, 2023 1934 -
Direct Preference Optimization with Synthetic Data on Anyscale Franklin Wang, Sumanth Hegde, Kourosh Hakhamaneshi Aug. 21, 2024 9249 1
Model Batch Inference in Ray: Actors, ActorPool, and Datasets Eric Liang, Jules S. Damji, Zhe Zhang Nov. 03, 2022 2084 4
Anyscale Endpoints: JSON Mode, Function calling, New models: Llama Guard and Mistral-7B-OpenOrca Endpoints Team Dec. 12, 2023 186 -
Loading Llama-2 70b 20x faster with Anyscale Endpoints Yi Cheng, Cade Daniel, Chen Shen, Liguang Xie Oct. 11, 2023 1961 5
Portkey ♥️ Anyscale Endpoints Endpoints Team Dec. 12, 2023 564 -
Getting Started with Distributed Machine Learning with PyTorch and Ray Michael Galarnyk, Richard Liaw, Robert Nishihara Mar. 02, 2021 1360 -
Scaling Model Batch Inference in Ray: Using Actors, ActorPool, and Ray Data Eric Liang, Jules S. Damji, Zhe Zhang May. 16, 2023 1856 -
Numbers every LLM Developer should know Waleed Kadous May. 17, 2023 1423 95
Handling files and packages on your cluster with Ray runtime environments Archit Kulkarni, Edward Oakes May. 05, 2022 860 -
Three ways to speed up XGBoost model training Antoni Baum, Chandler Gibbons Feb. 17, 2022 1609 -
Deep Dive: Data Ingest in a Third Generation ML Architecture Eric Liang, Chen Shen, Clark Zinzow, Waleed Kadous Nov. 30, 2021 1783 -
Automatic and optimistic memory scheduling for ML workloads in Ray Clarence Ng, Jules S. Damji Mar. 02, 2023 2423 -
Ray Summit 2022 Call for Papers is now open Jules S. Damji, Chandler Gibbons Mar. 23, 2022 585 -
Learn about Multi Armed Bandits and RL-based Recommender Systems at Ray Summit 2020 Dean Wampler, Pace Nathan Sep. 02, 2020 225 -
Ray Summit 2022 Stories - Large Language Models Anyscale Ray Team Feb. 16, 2023 680 -
LLM-based summarization: A case study of human, Llama 2 70b and GPT-4 summarization quality Justin Olsson, Waleed Kadous Nov. 09, 2023 1195 1
Welcome Keerti Robert Nishihara Jul. 31, 2024 743 2
Videos and Slides for the Third Ray Summit Connect, July 8, 2020 Dean Wampler Jul. 08, 2020 123 -
Offline Batch Inference: Comparing Ray, Apache Spark, and SageMaker Amog Kamsetty, Eric Liang, Jules S. Damji May. 04, 2023 2042 -
How Ikigai Labs Serves Interactive AI Workflows at Scale using Ray Serve Jaehyun Sim, Amar Shah Aug. 19, 2021 2040 -
Introducing Distributed LightGBM Training with Ray Antoni Baum, Will Drevo Aug. 10, 2021 1149 22
Introducing Elastic Distributed Training on Anyscale Matthew Deng, Justin Yu Jul. 22, 2024 478 -
Ray & MLflow: Taking Distributed Machine Learning Applications to Production Amog Kamsetty, Archit Kulkarni Jan. 13, 2021 1091 -
How to distribute hyperparameter tuning using Ray Tune Juan Navas, Richard Liaw Feb. 15, 2022 3064 -
Why I Joined Anyscale: Powering an Open Source AI Revolution Lance Walter Apr. 28, 2023 799 -
Anyscale Endpoints: JSON Mode and Function calling Features Endpoints Team Dec. 12, 2023 2050 2
Announcing Anyscale Private Endpoints and Anyscale Endpoints Fine-tuning Matt Connor, Robin Singh Oct. 24, 2023 467 3
Cloud Infrastructure for LLM and Generative AI Applications Yifei Feng, Sriram Sankar, Siddharth Venkatesh, Ameer Haj Ali Sep. 14, 2023 1868 4
Enterprise Applications of Reinforcement Learning: Recommenders and Simulation Modeling Ben Lorica Mar. 25, 2020 1497 -
Three Key Elements of a Scalable ML Platform Phi Nguyen Dec. 16, 2022 1733 -
How Ant Group uses Ray to build a Large-Scale Online Serverless Platform Tengwei Cai, Yang Liu, Chengxi Luo, Xiaofeng Yang Dec. 12, 2022 2353 3
Building RAG-based LLM Applications for Production Goku Mohandas, Philipp Moritz Oct. 25, 2023 10794 11
Announcing Ray 1.0 Eric Liang Sep. 30, 2020 439 3
Faster stable diffusion fine-tuning with Ray AIR Kai Fricke Mar. 28, 2023 1627 -
Challenges of deploying ML models in production Phi Nguyen Jul. 14, 2022 959 -
Trends in AI and Python Scalability: Reflections from the Ray Summit Program Chairs Dean Wampler, Ben Lorica Aug. 26, 2020 1021 -
Why I’m joining Anyscale Waleed Kadous Jan. 04, 2021 757 -
Announcing Aviary: Open Source Multi-LLM Serving Waleed Kadous May. 31, 2023 743 24
Reproducible Performance Metrics for LLM inference Waleed Kadous, Kyle Huang, Wendi Ding, Liguang Xie, Avnish Narayan, Ricky Xu Nov. 01, 2023 2495 2
Video and Code for Anyscale Academy: Ray Tune and Ray Serve, July 22, 2020 Sophia DeMartini Jul. 23, 2020 61 -
Ray Spotlight: How we delivered Ray weekly releases Sam Chan Jun. 25, 2024 629 -
Inspecting Sewer Line Safety Using Thousands of Hours of Video Lance Walter May. 22, 2023 814 -
Population Based Bandits: Provably Efficient Online Hyperparameter Optimization Jack Parker-Holder, Amog Kamsetty Nov. 16, 2020 1314 -
Training One Million Machine Learning Models in Record Time with Ray Eric Liang, Robert Nishihara Dec. 17, 2022 2124 1
Blue River Technology Developers Iterate 2.5X Faster with the Anyscale Fully-Managed Ray Platform Uday Kanwar, Deb Daipayan Feb. 27, 2023 608 -
Scaling Embedding Generation Pipelines From Pandas to Ray Data Marwan Sarieddine Sep. 04, 2024 2154 -
Fine-tuning Llama-3, Mistral and Mixtral with Anyscale Marwan Sarieddine and Kamil Kaczmarek Sep. 11, 2024 2256 -
Building a RAG Batch Inference Pipeline with Anyscale and Union Kevin Su and Kai-Hsun Chen Sep. 12, 2024 1665 -
Roblox Guest Blog: Fast and Efficient Online Model Serving Younes Abouelnagah Sep. 19, 2024 2925 -
RL for recommender systems Michael Galarnyk Jul. 20, 2021 769 -
Accelerated Metadata Fetching in Ray Data up to 4.5x Faster on Anyscale Balaji Veeramani, Hao Chen, Richard Liaw, Matthew Connor and Praveen Gorthy Oct. 01, 2024 607 -
Anyscale on Kubernetes: Simplifying AI Workloads on User-Managed Infrastructure Dominic Catalano and Yifei Feng Oct. 01, 2024 792 -
Anyscale Now Available on AWS Marketplace and Achieves Generative AI Competency The Anyscale Team Oct. 01, 2024 510 -
Batch LLM Inference on Anyscale slashes AWS Bedrock costs by up to 6x Cody Yu, Scott Lee, Ricky Xu, William Lin, Praveen Gorthy and Richard Liaw Oct. 01, 2024 1180 -
Ray Data GA Hao Chen, Richard Liaw and Praveen Gorthy Oct. 01, 2024 1037 -
Anyscale’s New User Experience: A Comprehensive Overview The Anyscale Team Oct. 01, 2024 1161 -
Anyscale Now on GCP Marketplace The Anyscale Team Oct. 01, 2024 381 -
Autoscaling Large AI Models up to 5.1x Faster on Anyscale Christopher Chou, Austin Kuo, Richard Liaw, Edward Oakes and Chris Sivanich Oct. 01, 2024 1260 -
Enterprise Governance and Observability on Anyscale The Anyscale Team Oct. 01, 2024 479 -
Announcing RayTurbo Akshay Malik, Praveen Gorthy and Richard Liaw Oct. 01, 2024 1453 -
Ray Summit 2024: Breaking Through the AI Complexity Wall The Anyscale Team Oct. 03, 2024 1600 -
Ray Compiled Graphs: Optimized AI Workloads with Native GPU Communication Sang Cho, Sam Chan and Stephanie Wang Oct. 07, 2024 1910 -
Unlocking the Power of Scalable Machine Learning with Anyscale and Astronomer The Anyscale Team Oct. 29, 2024 1063 -
Anyscale Named a Cool Vendor for AI Engineering by Gartner® The Anyscale Team Nov. 13, 2024 399 -

By Matt Makai. 2021-2024.