Open Source Artificial Intelligence Projects For GNU/Linux


Artificial intelligence is becoming more ingrained with the consumer market. Microsoft has Cortana, Apple has Siri and Amazon has Alexa as self-learning artificial intelligence projects. Self-driving cars are now becoming a reality thanks to AI driving technology. Even the marketing industry is taking advantage self-learning AI, as shown by Andy Fox of Element 7 Digital.

The disappointing reality of mainstream artificial intelligence is that it is being dominated by proprietary software. Industries may not give up their secrets so easily, which is why the open source community needs to support free AI projects that currently exist.

Why Use Linux?

Linux is not a household name for the majority of end users, but it widely appreciated by web hosters, researchers, and programmers. The security of Linux is much greater than Windows or OSX and it does not have any nasty surprises since the source code is public domain. It is also the most portable operating system since the kernel can be compiled and used by just about any architecture.

Considering the openness and security of Linux, wouldn’t you prefer that your self-driving car uses a more secure operating system? Even Google has been bitten by the Linux bug and is using their own Ubuntu variant for machine learning named Goobuntu.

Some Of The AI Projects For GNU/Linux

Lovers of FOSS and Linux will be pleased to know that there is a plethora of AI projects available for Linux. Most of these projects are machine learning libraries that can also be cross-platform for Windows, OSX or BSD variants.

Mycroft AI

Mycroft is the first project that aims to be an open source competitor to assistants like Siri or Cortana. Dubbed as the “AI For Everyone”, it is designed to run on any platform including automobiles or a Raspberry Pi. The framework is designed to learn from voice commands and will share the information with the project to help develop a better AI. The source code can be ran on any device that has a Python interpreter.


The Open Neural Networks Library (OpenNN) is an open source C++ library used specifically for deep machine learning. It’s architecture uses several layers of processing units for analytical learning. It supports acceleration by OpenMP and NVIDIA’s Cuda.


OpenCyc is one of the older AI projects and has been in production since 2001. It is a general knowledge AI that is particularly useful for trivia games, understanding text, and learning knowledge within specific domains.


NuPIC is an AI learning framework that is implementable into Python, C++, Java, Clojure, Go, or JavaScript. It gathers analytics from from live data streams to recognized time-based patterns. It is ideal for detecting anomalies within live data. Their HTM design is inspired by neuroscience.

Apache SystemML

Apache’s SystemML is an artificial intelligence framework that is available for R and Python. It is designed for big-data systems using high-level mathematical equations. It is currently being used by large industries like automotive or airport traffic control.


Deeplearning4j (Deep Learning for Java) is one of the leading open source AI libraries for Java and Scala. It is suitable for business applications and may be accelerated by CPUs or GPUs.


Caffe boasts as being one of the fastest of the deep learning framework. It is ideal for research projects needing quick processing of data and hardware acceleration. Its modular design allows it to easily be forked or extended and it is already been deployed in thousands of other projects.


H20 is designed for advanced decision making for large industries. It supports AI methods like gradient boosting, random forests and generalized linear.


MLlib is designed to run on Hadoop clusters and other distributed computing platforms. It comes with a variety of advanced algorithms and it compatible with Python, Java, Scala and R.

Since AI is becoming such a hot trend this day, it is inevitable that more open sourced projects will keep spawning. As more large corporations will realize the benefits of using Linux, we should expect to see more corporate funding amongst these open source projects as well. Also consider that since Linux has such portability, it may be the most desired operating system for AI solutions in embedded IoT devices in the near future.