Subject archive for "ray"
OpenAI demonstrated the profound impact generative AI could have. Such techniques turn datasets into transformative tools and products. Tangible AI projects that are both inspiring and can save your company time and money. Better yet, you are in a good position to aim high.
By Thomas Dinsmore and Yuval Zukerman5 min read
Translation between Skeletal formulae and InChI labels is a challenging image captioning problem, especially when it involves large amounts of noisy data. In this blog post we share our experience from the BMS molecular translation challenge and show that CPU-based distributed learning can significantly shorten model training times.
By Jennifer Davis14 min read
Apache Spark, Dask, and Ray are three of the most popular frameworks for distributed computing. In this blog post we look at their history, intended use-cases, strengths and weaknesses, in an attempt to understand how to select the most appropriate one for specific data science use-cases.
By Nikolay Manchev15 min read
By Dean Wampler13 min read
Dean Wampler provides a distilled overview of Ray, an open source system for scaling Python systems from single machines to large clusters. If you are interested in additional insights, register for the upcoming Ray Summit.
By Dean Wampler14 min read
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