首页|Patent Issued for Architecture to support color scheme-based synchronization for machine learning (USPTO 11995463)
Patent Issued for Architecture to support color scheme-based synchronization for machine learning (USPTO 11995463)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A patent by the inventors Durakovic, S enad (Palo Alto, CA, US), Nalamalapu, Gopal (Santa Clara, CA, US), Sodani, Avina sh (San Jose, CA, US), filed on April 22, 2021, was published online on May 28, 2024, according to news reporting originating from Alexandria, Virginia, by News Rx correspondents. Patent number 11995463 is assigned to Marvell Asia Pte Ltd. (Singapore, Singapor e). The following quote was obtained by the news editors from the background informa tion supplied by the inventors: "Applied Machine Learning (ML) is a booming fiel d that utilizes a cascade of layers of nonlinear processing units and algorithms for feature extraction and transformation with a wide variety of usages and app lications. ML typically involves two phases, training, which uses a rich set of training data to train a plurality of machine learning models, and inference, wh ich applies the trained machine learning models to actual applications. Each of the two phases poses a distinct set of requirements for its underlying infrastru ctures. Various infrastructures may be used, e.g., graphics processing unit (GPU ), a central processing unit (CPU), a Field Programmable Gate Array (FPGA), an A pplication Specific Integrated Circuit (ASIC), etc. Specifically, the training p hase focuses on, as a non-limiting example, GPU or ASIC infrastructures that sca le with the trained models and retraining frequency, wherein the key objective o f the training phase is to achieve high performance and reduce training time. Th e inference phase, on the other hand, focuses on infrastructures that scale with the applications, user, and data, and the key objective of the inference phase is to achieve energy (e.g., performance per watt) and capital (e.g., return on i nvestment) efficiency.
BusinessCyborgsEmerging TechnologiesMachine LearningMarvell Asia Pte Ltd
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