An IA is working on the route

Artificial Intelligence is sometimes working (or not) robots reproducing: what could possibly go wrong? cleaning robots quels sont les risques que cela ne fonctionne pas de manière optimale ? a timeline showing AI controversies (sept 2017 to oct 2018) of course cars will be running Linux

Machine Learning can be challenging wrong or incomplete/biased data leads to bad assumptions/results interpretation of insuficient data biased data provides biased results deep blue losing when debating

alphago for the game of Go GPL-3+ - written in C
Theano: BSD - widely used Python deep learning framework: Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy_.
Caffe: BSD 2-clause - widely used C+ + deep learning framework: Caffe is a deep learning framework made with expression, speed, and modularity in mind Torch: used by Google, AlphaGo and Facebook: Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. Google's large scale machine learning framework. Microsoft's deep learning toolkit.

FOSS neural network libraries, such as the ones in Weka or the 13 year old FANN library.
Weka: GPL-2+ - Java: Waikato Environment for Knowledge Analysis (Weka) is a popular suite of machine learning software written in Java, FANN: LGPL - Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. frameworks

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