H2O and NVIDIA reach an agreement to accelerate machine learning on GPU

Open source AI platform vendors H2O.Ai aim to help companies deploy deep learning to solve complex problems, the company announced that the GPU handling company NVIDIA established partnerships to optimize their products on the GPU platform. H2O's AI products are intended to increase the training speed of machine learning and deep learning models by up to 75 times. GPU integrated potential use cases include customer service, prevent fraud, financial advice, and healthcare individualization. H2O is a founding member of the GPU Open Analysis Plan, which is designed to create an open framework for data science on GPUs. As part of the plan, the H2O GPU version of the GPU version is compatible with the GPU data box (open GPU memory data box). H2O can read data frames and run machine learning directly in GPU memory. The program announced in May, in addition to H2O, also attracted BlazingDB, Graphistry, Continuum, Mapd, and GunRock, led by Cuda researcher John Owens. H2O CEO and Joint Founder SRI Ambati said: "H2O.ai is very happy to announce our constant development of NVIDIA to introduce explanation, fast and accurate algorithm into GPU. H2O.Ai with NVIDIA GPU acceleration function Enterprise AI communities bring high performance, cloud-neutral learning and reasoning stacks. " In the past five years, H2O has been used in more than 9,000 companies, including more than one-third of the company's 500 company. H2O Marketing Director Vinod Iyengar said that the open source model is very good to H2O. "If you don't use open source software, our company is not possible to have 9,000 organizations adopted by companies. We are gradually become a factual standard for machine learning and depth learning." The business model is designed to support production of companies using H2O. "The company has many models to put production; once this, they need our data science and production support." Ai Yang said. Read more

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