Language Selection

English French German Italian Portuguese Spanish

A Summary Between KDE Plasma 5.18 LTS And GNOME 3.36 Gresik

Filed under
KDE
GNOME

After publishing my latest GNOME and then Plasma articles, I think it is interesting to summarize between them in a separate article considering several interesting stuffs. First, their release date are the same, 11, except Plasma is in February and GNOME is in March. Second, they publish interesting videos and announcements I listed below. Third, they had conferences in 2019 that back them up namely Akademy and GNOME.Asia Summit I also listed below. Fourth, they have users who love to write reviews such as Dedoimedo and OMG! Ubuntu I listed below too. Last but not least, I also mentioned where to download their source code, to contribute to them, and the donation links. I wish this summary article helps you in figuring out more about both. Enjoy desktop GNU/Linux!

Read more

More in Tux Machines

Meet LBRY, A Blockchain-based Decentralized Alternative to YouTube

LBRY is a new Blockchain-based, open source platform for sharing digital content. It is gaining popularity as a decentralized alternative to YouTube but LBRY is more than just a video sharing service. Read more

Android Leftovers

Top 10 Circuit design tools for Linux

So, you are planning a new electronics project and wonder what tools are the best? You may also be learning to design your own circuits and your favourite platform is Linux. Where are the Linux specific, or cross-platform tools, and which one suits my needs the best? Today, you will learn what you need to get started with your new project. This list goes through the tools available and discusses the pros and cons of each. You will also hear about how they specialise. Before you start, you may want to consider what your current goals are. Are you learning to create hobby projects or are you already bringing your game to a higher level? You may also want to consider if your favourite electronics supplier already supports the tool you are going to make. Many of these tools import catalogues to the application so you can browse while designing, making it very convenient to order boards or components. Read more

MindSpore Source Code

  • Huawei open sources MindSpore: claims to provide 'all-scenario AI computing framework'

    Huawei made a series of important announcements at the Huawei Developer Conference 2020 (Cloud) – HDC.Cloud, on March 28, notably that MindSpore, the all-scenario AI computing framework, goes open source on Gitee, and that ModelArts Pro, the first-ever AI app development suite for enterprises, goes live on HUAWEI CLOUD. Huawei also showcased some of the significant applications for Huawei's Atlas AI computing platform, on the cloud, edge, and devices. In doing so, Huawei has delivered the full-stack, all-scenario AI solutions for developers that it had first unveiled at HUAWEI CONNECT 2018.

  • Huawei open-sources AI framework MindSpore to rival Google’s TensorFlow

    China’s Huawei Technologies Co. Ltd. today said it has open-sourced a framework for artificial intelligence-based application development called MindSpore. First revealed last year, MindSpore is an alternative to well known AI frameworks such as Google LLC’s TensorFlow and Facebook Inc.’s PyTorch. It can scale across devices, cloud and edge environments, Huawei said in a statement. The code is now available to download on GitHub and Gitee.

  • Huawei open-sources TensorFlow competitor MindSpore
  • Huawei Makes TensorFlow Competitor MindSpore Open Source

    Huawei has made its MindSpore AI framework open source. The Chinese tech giant is competing with the well-known AI frameworks from Google and Facebook, with a large number of advantages that ‘Ai algorithms as-a-code’ can provide. In a statement, the Chinese tech giant states that its MindSpore AI framework is suitable for developing AI applications. The AI ​​framework – co-developed with universities in Beijing and the United Kingdom and with a Turkish start-up – can easily be rolled out in various environments, such as on devices, within (multi) cloud and edge environments. Huawei launched the new AI framework last year in conjunction with the Ascend 910 processor. The AI ​​chip provides 256 teraflops of computing power on FP16, and that at a power consumption of 350 watts. With MindSpore and the Ascend 910 in addition to that new chip, the company has the most important components in the hands of a full AI stack.