===An IA is working on the route===
Artificial Intelligence is sometimes working (or not)

https://hardware.slashdot.org/story/21/11/29/229210/worlds-first-living-robots-can-now-reproduce-scientists-say robots reproducing: what could possibly go wrong?

https://hardware.slashdot.org/story/21/11/19/2135251/alphabet-puts-prototype-robots-to-work-cleaning-up-googles-offices cleaning robots

https://www.theguardian.com/technology/2021/mar/08/typographic-attack-pen-paper-fool-ai-thinking-apple-ipod-clip


https://yro.slashdot.org/story/19/09/08/1347225/one-of-americas-biggest-markets-for-ai-powered-security-cameras-schools

https://tech.slashdot.org/story/19/04/02/1928231/can-we-stop-ai-outsmarting-humanity
https://tech.slashdot.org/story/19/04/02/1942221/google-employees-are-lining-up-to-trash-googles-ai-ethics-council

https://tech.slashdot.org/story/19/04/02/0347232/researchers-trick-tesla-autopilot-into-steering-into-oncoming-traffic

https://tech.slashdot.org/story/19/03/07/1935238/researchers-are-training-image-generating-ai-with-fewer-labels
https://news.slashdot.org/story/19/03/05/2119250/google-open-sources-gpipe-a-library-for-training-large-deep-neural-networks

https://www.technologyreview.com/s/530276/hidden-obstacles-for-googles-self-driving-cars/
https://tech.slashdot.org/story/19/03/06/2157221/self-driving-cars-may-hit-people-with-darker-skin-more-often-study-finds
https://tech.slashdot.org/story/19/03/05/1711217/volvo-to-test-full-size-driverless-bus-in-singapore

https://tech.slashdot.org/story/19/03/03/0037251/tesla-angers-autonomous-vehicle-experts-by-promising-full-self-driving-model-3

https://news.slashdot.org/story/19/03/04/1811231/thousands-in-london-face-incorrect-benefit-cuts-from-automated-fraud-detector quels sont les risques que cela ne fonctionne pas de manière optimale ?

https://developers.slashdot.org/story/19/02/12/1756206/ibm-says-watson-ai-services-will-now-work-on-any-cloud

https://cdn.technologyreview.com/i/images/timeline-ai-now_1.jpg?sw=2000&cx=0&cy=0&cw=2000&ch=1125 a timeline showing AI controversies (sept 2017 to oct 2018)

https://tech.slashdot.org/story/19/01/05/1928205/linux-for-cars-tesla-isnt-the-only-automaker-running-linux-under-the-hood of course cars will be running Linux

== Machine Learning can be challenging ==
https://tech.slashdot.org/story/19/03/06/172204/google-tool-lets-any-ai-app-learn-without-taking-all-your-data

https://science.slashdot.org/story/19/02/16/2028229/misleading-results-from-widely-used-machine-learning-data-analysis-techniques wrong or incomplete/biased data leads to bad assumptions/results

https://yro.slashdot.org/story/19/02/16/1936219/report-that-tesla-autopilot-cuts-crashes-by-40-called-bogus interpretation of insuficient data
https://yro.slashdot.org/story/19/02/16/0613252/academics-confirm-major-predictive-policing-algorithm-is-fundamentally-flawed biased data provides biased results

https://tech.slashdot.org/story/19/02/14/199200/this-person-does-not-exist-website-uses-ai-to-create-realistic-yet-horrifying-faces

https://developers.slashdot.org/story/19/02/12/1930210/ubisoft-and-mozilla-announce-ai-coding-assistant-clever-commit

https://slashdot.org/story/19/02/12/145208/ibms-ai-loses-to-a-human-debater deep blue losing when debating



=== alphago for the game of Go ===
https://linuxfr.org/users/wilk/journaux/alphago-remporte-le-premier-match-contre-lee-sedol

http://developers.slashdot.org/story/16/03/13/1346215/gnu-project-introduces-gneural-network-ai-package
http://www.gnu.org/software/gneuralnetwork/ GPL-3+ - written in C
Theano: http://deeplearning.net/software/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: http://caffe.berkeleyvision.org/ BSD 2-clause - widely used C+ + deep learning framework: Caffe is a deep learning framework made with expression, speed, and modularity in mind
~- Demo: http://demo.caffe.berkeleyvision.org/
~- Code: https://github.com/BVLC/caffe/
Torch: http://torch.ch/ 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.
~- Doc: http://torch.ch/docs/getting-started.html
~- Code: https://github.com/torch/torch7
https://www.tensorflow.org/ Google's large scale machine learning framework.
https://github.com/Microsoft/CNTK Microsoft's deep learning toolkit.

FOSS neural network libraries, such as the ones in Weka or the 13 year old FANN library.
Weka: http://www.cs.waikato.ac.nz/~ml/weka/ GPL-2+ - Java: Waikato Environment for Knowledge Analysis (Weka) is a popular suite of machine learning software written in Java,
~- Doc: http://www.cs.waikato.ac.nz/~ml/weka/documentation.html
~- Code: http://www.cs.waikato.ac.nz/~ml/weka/downloading.html (at sourceforge :/)
FANN: http://leenissen.dk/fann/wp/ 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.
~- Doc: http://leenissen.dk/fann/html/index.html
~- Code: http://leenissen.dk/fann/wp/download/


http://www.lorienpratt.com/amazon-announces-machine-learning-for-aws/

https://www.journaldunet.com/solutions/dsi/1487532-ces-ia-offertes-par-les-gafam-en-open-source/ frameworks



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CategoryTechnologySurvey