Language Selection

English French German Italian Portuguese Spanish

Why I Use Gentoo: Conclusion

Filed under
Gentoo

Of all the myriad Linux distributions out there, I’ve chosen Gentoo as the one to use on my primary desktop computer. Throughout this series, I’ve talked some of the reasons that I enjoy using Gentoo. As an incredibly brief summary, Gentoo fits my needs as a developer-oriented distribution with rolling upgrades.

That’s not to say that Gentoo is necessarily my favorite distribution in every arena. For most users who require nothing more than a functional, top-notch desktop distribution, I think Ubuntu is still at the forefront. Its non-rolling release cycle means that the user won’t necessarily have the latest versions of packages and must deal with a major upgrade every few months, but those are largely painless.

rest here




More in Tux Machines

France: ‘tax source code will be made public’

France’s tax department is willing to make the source code available for its income tax software system, says Axelle Lemaire, minister responsible for Digital Affairs. However, preparation takes time, she told April, France’s free software advocacy group, last month. Read more

Simplicity Linux 15.7 Comes at the End of July with Linux Kernel 4.0

David Purse from the development team of Simplicity Linux, a distribution derived from LXPup and built around the LXDE desktop environment, has announced the release of the first Beta build towards the final version of Simplicity Linux 15.7. Read more

Linux Kernel 3.14.46 LTS Has ARM and ARM64 Improvements, Updated Drivers

After announcing the release of the Linux kernel 4.1.1, Linux kernel 4.0.7, and Linux kernel 3.10.82 LTS, Greg Kroah-Hartman also published details about a new maintenance release of the Linux 3.14 kernel branch. Read more

Google open-sources its software for making trippy images with deep learning

The deepdream project is now available on GitHub. The project relies on the open-source Caffe deep learning framework. Deep learning involves training artificial neural networks on a large pile of data — for example, pictures of geese — and then throwing them a new piece of data, like a picture of an ostrich, to receive an educated guess about it. Read more