|
How ByteDance Scales Offline Inference with multi-modal LLMs to 200 TB Data
|
Amog Kamsetty, Hao Chen, Liguang Xie |
2023-08-14 |
1,872 |
7
|
|
Llama 2 is about as factually accurate as GPT-4 for summaries and is 30X cheaper
|
Waleed Kadous |
2023-08-23 |
2,933 |
19
|
|
How ThirdAI uses Ray for Parallel Training of Billion-Parameter Neural Networks on Commodity CPUs
|
Vihan Lakshman, Pratik Pranav, Siddharth Jain, Tharun Medini |
2023-08-29 |
1,643 |
78
|
|
Fine-Tuning LLMs: LoRA or Full-Parameter? An in-depth Analysis with Llama 2
|
Artur Niederfahrenhorst, Kourosh Hakhamaneshi, Rehaan Ahmad |
2023-09-06 |
3,597 |
22
|
|
Anyscale and Meta Collaborate to Advance the Llama-2 Ecosystem
|
Robert Nishihara, Joe Spisak |
2023-09-07 |
325 |
--
|
|
Cloud Infrastructure for LLM and Generative AI Applications
|
Yifei Feng, Sriram Sankar, Siddharth Venkatesh, Ameer Haj Ali |
2023-09-14 |
1,868 |
4
|
|
Fast, flexible, and scalable data loading for ML training with Ray Data
|
Stephanie Wang, Scott Lee, Cheng Su, Hao Chen, Eric Liang |
2023-09-15 |
3,238 |
4
|
|
Ray 2.7 features major stability improvements to Ray AI Libraries and KubeRay and introduces RayLLM
|
Jules S. Damji, Richard Liaw |
2023-09-18 |
1,798 |
--
|
|
Ray Serve: Tackling the cost and complexity of serving AI in production
|
Akshay Malik, Edward Oakes, Phi Nguyen |
2023-09-25 |
2,392 |
--
|
|
Loading Llama-2 70b 20x faster with Anyscale Endpoints
|
Yi Cheng, Cade Daniel, Chen Shen, Liguang Xie |
2023-10-11 |
1,961 |
3
|
|
Llama, Scaling Up LLMs in an Open Ecosystem
|
Anyscale Ray Team |
2023-10-16 |
1,246 |
--
|
|
Building Context-Aware Reasoning Applications with LangChain and LangSmith
|
Anyscale Ray Team |
2023-10-18 |
1,214 |
--
|
|
Practical Data Considerations for Building Production-Ready LLM Applications
|
Anyscale Ray Team |
2023-10-19 |
1,116 |
--
|
|
Heterogeneous Training Cluster with Ray at Netflix
|
Anyscale Ray Team |
2023-10-20 |
902 |
--
|
|
Announcing Anyscale Private Endpoints and Anyscale Endpoints Fine-tuning
|
Matt Connor, Robin Singh |
2023-10-24 |
467 |
3
|
|
Building Production AI Applications with Ray Serve
|
Anyscale Ray Team |
2023-10-24 |
1,213 |
--
|
|
Building RAG-based LLM Applications for Production
|
Goku Mohandas, Philipp Moritz |
2023-10-25 |
10,794 |
2
|
|
Optimizing LLM Training with Airbnb's Next-Gen ML Platform
|
Anyscale Ray Team |
2023-10-30 |
1,048 |
--
|
|
Reproducible Performance Metrics for LLM inference
|
Waleed Kadous, Kyle Huang, Wendi Ding, Liguang Xie, Avnish Narayan, Ricky Xu |
2023-11-01 |
2,495 |
2
|
|
Advances in Foundation Models — Technology, Society, and Applications
|
Anyscale Ray Team |
2023-11-03 |
1,460 |
--
|
|
Ray 2.8 features Ray Data extensions, AWS Neuron cores support, and Dashboard improvements
|
Jules S. Damji, Richard Liaw |
2023-11-07 |
791 |
--
|
|
LLM-based summarization: A case study of human, Llama 2 70b and GPT-4 summarization quality
|
Justin Olsson, Waleed Kadous |
2023-11-09 |
1,195 |
1
|
|
Inference Graphs at LinkedIn Using Ray-Serve
|
Anyscale Ray Team |
2023-11-09 |
1,267 |
--
|
|
How Spotify Built a Robust Ray Platform with a Frictionless Developer Experience
|
Anyscale Ray Team |
2023-11-09 |
1,259 |
--
|
|
Building an LLM-powered GitHub bot to improve your pull requests
|
Max Pumperla |
2023-11-15 |
3,491 |
--
|
|
Open Source LLMs: Viable for Production or a Low-Quality Toy?
|
Anyscale Ray Team |
2023-11-20 |
855 |
--
|
|
Anyscale and Lambda - Addressing AI Scarcity with Engineering
|
Anyscale team |
2023-11-21 |
585 |
--
|
|
Update on Ray CVEs CVE-2023-6019, CVE-2023-6020, CVE-2023-6021, CVE-2023-48022, CVE-2023-48023
|
Anyscale team |
2023-11-30 |
508 |
--
|
|
Anyscale Endpoints: Embedding endpoint, Llama-2 70B fine-tuning and improved sign-up experience
|
Anyscale team |
2023-11-30 |
376 |
--
|
|
Anyscale Endpoints: JSON Mode and Function calling Features
|
Endpoints Team |
2023-12-12 |
2,050 |
2
|
|
Portkey ♥️ Anyscale Endpoints
|
Endpoints Team |
2023-12-12 |
564 |
--
|
|
Anyscale Endpoints: JSON Mode, Function calling, New models: Llama Guard and Mistral-7B-OpenOrca
|
Endpoints Team |
2023-12-12 |
186 |
--
|
|
Comparing LLM performance: Introducing the Open Source Leaderboard for LLM APIs
|
Anyscale team |
2023-12-21 |
1,202 |
2
|
|
RAG at Scale: 10x Cheaper Embedding Computations with Anyscale and Pinecone
|
Scott Lee, Kyle Huang, Cheng Su, Hao Chen |
2024-01-16 |
995 |
1
|
|
Fine-tuning LLMs for longer context and better RAG systems
|
Artur Niederfahrenhorst, Kourosh Hakhamaneshi |
2024-02-13 |
2,847 |
1
|
|
Low-latency Generative AI Model Serving with Ray, NVIDIA Triton Inference Server, and NVIDIA TensorRT-LLM
|
Neelay Shah, Akshay Malik |
2024-03-13 |
642 |
--
|
|
Update on Ray CVE-2023-48022: New Verification Tooling Available
|
Anyscale team |
2024-03-27 |
606 |
--
|
|
Accelerating AI: Harnessing Intel(R) Gaudi(R) 3 with Ray 2.10
|
Ramit Hora |
2024-04-09 |
596 |
--
|
|
Ray Summit 2024 Call for Proposals is now open
|
Anyscale team |
2024-04-19 |
264 |
--
|
|
Reducing the Cost of Pre-training Stable Diffusion by 3.7x with Anyscale
|
Yunxuan Xiao, Hao Chen |
2024-05-09 |
2,176 |
5
|
|
Processing 2 Billion Images for Stable Diffusion Model Training - Definitive Guides with Ray Series
|
Max Pumperla, Marwan Sarieddine |
2024-05-14 |
4,209 |
--
|
|
Easily Debug Ray Applications with Ray Distributed Debugger
|
Anyscale team |
2024-05-15 |
624 |
--
|
|
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 |
2024-05-21 |
4,553 |
--
|
|
Cross-modal Search for E-commerce: Building and Scaling a Cross-Modal Image Retrieval App
|
Marwan Sarieddine, Natalia Czerep, Mateusz Kwasniak, Artur Zygadło |
2024-06-04 |
3,253 |
--
|
|
Ray Spotlight Series: Multitenant Serve Applications with Runtime Envs as Containers
|
Sam Chan, Cindy Zhang |
2024-06-13 |
800 |
--
|
|
End-to-end LLM Workflows Guide
|
Goku Mohandas |
2024-06-17 |
4,910 |
1
|
|
Ray Spotlight: How we delivered Ray weekly releases
|
Sam Chan |
2024-06-25 |
629 |
--
|
|
Building an LLM Router for High-Quality and Cost-Effective Responses
|
Amjad Almahairi |
2024-07-01 |
4,430 |
1
|
|
Deploy Ray Serve with up to 50% fewer nodes using Anyscale Replica Compaction
|
Matt Connor, Akshay Malik, Cindy Zhang |
2024-07-15 |
883 |
--
|
|
New on Anyscale: Debug and Optimize Ray Applications Faster with Structured Logging
|
Jiajun Yao, Kai-Hsun Chen |
2024-07-16 |
449 |
--
|