Posts with the tag Free Software:

SymPy: a powerful math library

SymPy is a lightweight symbolic mathematics library for Python under the 3-clause BSD license that can be used either as a library or in an interactive environment. It features symbolic expressions, solving equations, plotting and much more!

A Truly Free AI

Understanding what makes a software Free (as in freedom) has been going on since the beginning of the Free Software movement in the 80’s (at least). This led to the Free Software licenses, which help users to control the technology they use. However, considering the peculiarities of Artificial Intelligence (AI) software, one may wonder whether those licenses account for those. Free Software licenses were designed so that users control technology, and facilitate their collaboration.

Computers can't sustain themselves

The situation where an unskilled user can enjoy a well-working computer does only last so long.1 Either the user becomes good at maintaining the computer, or it will stop working correctly. That’s because computers are not reliable. If not used carefully, at some point, they will behave unexpectedly or stop working. Therefore, one will have to get their hands dirty and most likely learn something along the way. Some operating systems are more prone to gathering cruft, though.

How to install the original Doom on Fedora 31

If you want to distance yourself from the craziness of the world around and happen to be a computer geek, only a few things are more satisfying than blasting hordes of demons on Doom. Here is how to install GZDoom - an OpenGL port of Doom released under the GPLv3 license - and a mod called Brutal Doom on Fedora 31.

On Deep Learning and Free Software

As Deep learning is becoming more and more popular, there is an ongoing debate on whether it’s possible to create Deep Learning applications with a Free Software license. See for example this discussion on the debian-devel mailing list. The argument we often see is that: It’s impossible to study the inner workings of a Deep Learning software (for example, an image classifier or a text generator) or improve it, because one cannot understand how it’s going to make predictions only by looking at the weights of the Deep Learning model Training a Deep Learning model requires a specialized and expensive hardware that runs non-Free software But the first statement misses the point of Deep Learning programs.