In recent years, mobile devices have gained increasingly development with stronger computation capability and larger storage. Some of the computation-intensive machine learning and deep learning tasks can now be run on mobile devices. To take advantage of the resources available on mobile devices and preserve users' privacy, the idea of mobile distributed machine learning is proposed. It uses local hardware resources and local data to solve machine learning sub-problems on mobile devices, and only uploads computation results instead of original data to contribute to the optimization of the global model. This architecture can not only relieve computation and storage burden on servers, but also protect the users' sensitive information. Another benefit is the bandwidth reduction, as various kinds of local data can now participate in the training process without being uploaded to the server. In this paper, we provide a comprehensive survey on recent studies of mobile distributed machine learning. We survey a number of widely-used mobile distributed machine learning methods. We also present an in-depth discussion on the challenges and future directions in this area. We believe that this survey can demonstrate a clear overview of mobile distributed machine learning and provide guidelines on applying mobile distributed machine learning to real applications.
Windows 10 is becoming a useful Unix/Linux sysadmin platform. First, it has incorporated Windows Subsystem for Linux in the Windows 10 Fall Creators Update. Now, in the Windows 10 April 2018 Update, Microsoft has finally brought a native Secure Shell (SSH) to Windows. It's taken a long time. Microsoft started work on porting OpenSSH to PowerShell in 2015 because of user demand.
The platform can share GPUs in a virtualized infrastructure, as a pool of network-accessible resources, rather than isolated resources per server. Bitfusion also supports other accelerators such as Field Programmable Gate Arrays (FPGAs) and Application-Specific Integrated Circuits (ASICs). Bitfusion works across AI frameworks, clouds, networks, and formats such as virtual machines and containers.
A malicious Google Chrome extension that can recognize and steal payment card details entered in web forms is still available on the Chrome Web Store. The extension is the work of a cyber-criminal group and has been at the heart of a malware distribution effort in the past. The website through which the extension was initially distributed is now down, but the extension is still available on the Play Store, meaning it could be used for future campaigns to infect new users. Until now, the extension has been installed by roughly 400 users, according to stats available on its official Chrome Web Store listing. The extension's name is Flash Reader.