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Cooperatively operating a network of supervised learning processors to concurrently distribute supervised learning processor training and provide predictive responses to input data

机译:合作操作监督学习处理器网络,以同时分发监督学习处理器培训,并为输入数据提供预测响应

摘要

A supervised learning processing (SLP) system and non-transitory, computer program product provides cooperative operation of a network of supervised learning processors to concurrently distribute supervised learning processor training, generate predictions, and provide prediction driven responses to input objects, such as NL statements. The SLP system includes SLP stages that are distributed across multiple SLP subsystems. Concurrently training SLP's provides accurate predictions of input objects and responses thereto, the SLP system and non-transitory, computer program product enhance the network by providing high quality value predictions and responses and avoiding potential training and operational delays. The SLP system can enhance the network of SLP subsystems by providing flexibility to incorporate multiple SLP models into the network and train at least a proper subset of the SLP models while concurrently using the SLP system and non-transitory, computer program product in commercial operation.
机译:监督学习处理(SLP)系统和非暂时性,计算机程序产品提供了监督学习处理器网络的协作操作,以便同时分发监督的学习处理器训练,生成预测,并为输入对象提供预测驱动的响应,例如NL语句。 SLP系统包括跨多个SLP子系统分布的SLP阶段。同时训练SLP提供了对输入对象的准确预测,并通过提供高质量的值预测和响应并避免潜在的训练和操作延迟来提高网络,并避免潜在的训练和运营延迟,提供准确的输入对象和响应的预测。 SLP系统可以通过提供灵活性来增强SLP子系统的网络,以便将多个SLP模型结合到网络中,并在商业操作中同时使用SLP系统和非暂时的计算机程序产品携带SLP模型的至少适当的SLP模型子集。

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