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GNOME: Endless OS 3.4, Flatpak 1.8 and Lots of Hackfesting

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GNOME
  • Endless OS 3.4 Released With New Features, Linux 4.15, And Phone Companion App

    Founded in 2011, Endless Mobile, Inc. develops Linux-based Endless OS and hardware running the same. The firm has recently shipped Endless OS 3.4, the latest and major release of the operating system.

  • Flatpak 1.8 FreeDesktop.org Runtime Is Yocto-Free, Powered By BuildStream

    The current Flatpak runtimes are based upon the 1.6 FreeDesktop.org runtime but a major new version is in the works.

    Unlike the current Freedesktop runtime where the lower-layer is built using Yocto and the upper-layer built with Flatpak-Builder, the new 1.8 Freedesktop runtime is making use of BuildStream.

  • Introducing the 1.8 freedesktop runtime in the gnome nightly builds

    All the current Flatpak runtimes in wide use are based on the 1.6 Freedesktop runtime. This is a two-layered beast where the lower layer is built using Yocto and the upper layer is built using flatpak-builder.

  • GNOME's 2018 Performance Hackfest Wraps Up In Cambridge

    GNOME's 2018 Performance Hackfest is wrapping up today in Cambridge, UK after spending the past few days focusing on how to better optimize the desktop stack for RAM/CPU/GPU/power efficiency. The fruits of this hackfest will hopefully become apparent with the GNOME 3.30 release due out this September.

    The GNOME Foundation and Raspberry Pi Foundation put on this latest developer gathering to focus on improving GNOME's performance. Among their work was looking at how to improve the graphics performance of GNOME Shell, reducing system memory usage, looking at slow I/O issues, and more.

  • Fractal Hackfest in Strasbourg

    Last week we had an intense 4-day hackfest in Strasbourg to map out the future of Fractal, a native GNOME Matrix messaging app. The event was held at Epitech in Strasbourg’s old town, and organized by Alexandre Franke. Among the attendees were core Fractal contributors Daniel, Alexandre, Eisha, and Julian, as well as Dorota, Adrien, and Francois from Purism. Special thanks go to Matthew from the Matrix core team for joining us on the first two days.

  • Internationalization of Fractal (part 2)

    For my investigations, I first tried to write a textual program that works with gettext. I spent quite some time to figure out how all of this works but I finally was able to make it work. And that means that we should be able to implement i18n for Fractal using gettext!

  • GNOME Performance Hackfest

    We’re about to finish the three days long first GNOME Performance Hackfest here in Cambridge.

    We started covering a few topics, there are three major areas we’ve covered and in each one of those there has been a bunch of initiatives.

  • GIMP 2.10.0 is out!

    So we are a bit late to announce it, since this happened on April 27, during Libre Graphics Meeting 2018 (by the way, can you spot ZeMarmot team, Aryeom and Jehan, in the goodbye photo of the meeting?), but yeah after 6 years of hard work, GIMP 2.10.0 is finally out!

    This is a huge release. You can read the release notes which are scrolling like forever and that is still not actually the full deal. We had so many awesome changes and cool new features in this release that we had to cut down the release notes contents when writing it.

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TransmogrifAI From Salesforce

  • Salesforce plans to open-source the technology behind its Einstein machine-learning services
    Salesforce is open-sourcing the method it has developed for using machine-learning techniques at scale — without mixing valuable customer data — in hopes other companies struggling with data science problems can benefit from its work. The company plans to announce Thursday that TransmogrifAI, which is a key part of the Einstein machine-learning services that it believes are the future of its flagship Sales Cloud and related services, will be available for anyone to use in their software-as-a-service applications. Consisting of less than 10 lines of code written on top of the widely used Apache Spark open-source project, it is the result of years of work on training machine-learning models to predict customer behavior without dumping all of that data into a common training ground, said Shubha Nabar, senior director of data science for Salesforce Einstein.
  • Salesforce open-sources TransmogrifAI, the machine learning library that powers Einstein
    Machine learning models — artificial intelligence (AI) that identifies relationships among hundreds, thousands, or even millions of data points — are rarely easy to architect. Data scientists spend weeks and months not only preprocessing the data on which the models are to be trained, but extracting useful features (i.e., the data types) from that data, narrowing down algorithms, and ultimately building (or attempting to build) a system that performs well not just within the confines of a lab, but in the real world.