Storage saving using CNNs**********

这项提议是朝着利用人工智能开发更高效的存储系统迈出的一步。目标是与高通加拿大公司的技术人员合作，开发能够使用最新的机器学习创新来更智能地使用存储资源的存储系统。*实现这一目标的一种方法是将通信设备所需的信息子集存储在存储设备上。这个子集稍后将由智能系统用来构建完整的子集。机器学习解决方案将是这一智能系统的核心。*这项建议建议使用卷积神经网络(或简称CNN)来建立一个系统，其中训练阶段将教会系统如何使用部分数据集来产生缺失的部分。然后，将对该系统进行测试和适当调整，以实现高精度和高效率。*加拿大高科技部门将从这项提案的结果中受益，因为它为建立更好的存储系统提供了解决方案，几乎所有科技公司都在使用它。************

This proposal is a step towards employing AI in developing more efficient storage systems. The goal is to collaborate with technical staff from Qualcomm Canada to develop storage systems capable of using the latest machine learning innovations to use storage resources more intelligently.****One way to do so is to store a subset of the information needed by communication devices on the storage. This subset will be used later by an intelligent system to build the complete set. Machine learning solutions will serve at the core of this intelligent system. ****This proposal suggests using Convolutional Neural Networks (or simply CNNS) to build a system where a training phase will teach the system how to use part of the data set to produce the missing portion. The system will then be tested and properly tuned to achieve high accuracy and efficiency.****Canada's high-tech sector will benefit from the findings of this proposal as it provides solutions to building better storage systems which are virtually used by all technological companies. ************