XAI/NLG

Fokus liegt auf explainable trough natural/artistic language

XAI Links

• https://de.m.wikipedia.org/wiki/Explainable_Artificial_Intelligence
• https://netzpolitik.org/2018/enquete-kommission-kuenstliche-intelligenz-sachverstaendige-und-abgeordnete-klaeren-grundbegriffe/
• https://www.ayasdi.com/blog/artificial-intelligence/trust-challenge-explainable-ai-not-enough/
• https://www.bons.ai/blog/explainable-artificial-intelligence-using-model-induction
• https://en.m.wikipedia.org/wiki/Right_to_explanation
• https://bdtechtalks.com/2018/09/25/explainable-interpretable-ai/
• RISE: https://bdtechtalks.com/2018/10/15/kate-saenko-explainable-ai-deep-learning-rise/
• DARPA: https://www.darpa.mil/program/explainable-artificial-intelligence

NLG Links

• https://github.com/dangeng/Simple_Adversarial_Examples
• https://bdtechtalks.com/2018/02/20/ai-machine-learning-nlg-nlp/
• https://www.wired.com/2016/03/google-inbox-auto-answers-emails/
• https://bdtechtalks.com/2017/08/21/rob-high-ibm-watson-cto-artificial-intelligence-chatbots/
• https://chatbotsmagazine.com/contextual-chat-bots-with-tensorflow-4391749d0077
  • Jupyter Notebook: https://github.com/ugik/notebooks/blob/master/Tensorflow%20chat-bot%20model.ipynb
• Facebook-Messenger-Bot: https://dzone.com/articles/how-i-used-deep-learning-to-train-a-chatbot-to-tal
  • Git-Repo: https://github.com/adeshpande3/Facebook-Messenger-Bot
• https://tutorials.botsfloor.com/how-to-build-your-first-chatbot-c84495d4622d
  • Jupyter Notebooks: https://github.com/suriyadeepan/practical_seq2seq