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Anyscale Announces $40M in Series B Funding Led by NEA
Creators of the Ray Open Source Project Raise Capital to Define New Software Development Category and Bring First Commercial Offering to Market
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Why I joined Anyscale
A bold vision — to make distributed computing simple and accessible from anywhere. Open source model, with a developer-first mindset. A vibrant and rapidly growing community. And a stellar team, with a track record of building great technology to solve hard problems.
Attention Nets and More with RLlib's Trajectory View API
April 21, 2021Online Resource Allocation with Ray at Ant Group
March 30, 2021How to Speed Up Pandas with Modin
March 3, 2021Getting Started with Distributed Machine Learning with PyTorch and Ray
Ray is a popular framework for distributed Python that can be paired with PyTorch to rapidly scale machine learning applications.
Data Processing Support in Ray
February 16, 2021Retrieval Augmented Generation with Huggingface Transformers and Ray
Huggingface Transformers recently added the Retrieval Augmented Generation (RAG) model, a new NLP architecture that leverages external documents (like Wikipedia) to augment its knowledge and achieve state of the art results on knowledge-intensive tasks. In this blog post, we introduce the integration of Ray, a library for building scalable applications, into the RAG contextual document retrieval mechanism. This speeds up retrieval calls by 2x and improves the scalability of RAG distributed fine-tuning.
How to Speed up Scikit-Learn Model Training
February 3, 2021