Weekly Review 14 December 2016

Below are some of the interesting links I Tweeted about in the last week.

1. How AI, and the economy, are evolving together: https://techcrunch.com/2016/12/04/artificial-intelligence-and-the-evolution-of-the-fractal-economy/
2. OpenAI's Universe, a universal training ground for AI: http://www.theregister.co.uk/2016/12/05/openai_universe_reinforcement_learning/ 
3. A basic over-view of what AI is: https://techcrunch.com/2016/12/04/wtf-is-ai/ 
4. Doesn't seem to be an awful lot of AI in this AI marketing assistant: https://techcrunch.com/2016/12/05/meet-aiden-your-new-ai-coworker/ 
5. Free ebooks on machine learning and data analysis: http://www.kdnuggets.com/2016/12/packt-free-ebooks-machine-learning-python-data-analysis.html 
6. General AI is still a long way off: https://techcrunch.com/2016/12/05/deepmind-ceo-mustafa-suleyman-says-general-ai-is-still-a-long-way-off/ 
7. Uber is expanding its AI research: http://www.techrepublic.com/article/with-launch-of-uber-ai-labs-ride-sharing-giant-aims-to-expand-ai-research-beyond-autonomous-cars/ 
8. Amazon Go grocery shop uses AI instead of cashiers: http://www.techrepublic.com/article/amazon-go-grocery-store-replaces-cashiers-with-automation-and-ai/ 
9. Using AI to search for a better treatment for ALS: https://techcrunch.com/2016/12/06/benevolentbios-artificial-intelligence-could-discover-a-better-treatment-for-als/ 
10. Identity thieves are now using machine learning: https://www.datanami.com/2016/12/05/ai-will-spoof-steal-identify/ 
11. 8 essential software tools for data scientists: http://www.datasciencecentral.com/profiles/blogs/8-essential-tools-for-data-scientists 
12. Common statistical mistakes computer scientists make: http://www.cs.cornell.edu/~asampson/blog/statsmistakes.html 
13. Many AI models are still black boxes: http://www.zdnet.com/article/inside-the-black-box-understanding-ai-decision-making/ 
14. An AI that plays the FreeCiv strategy game at human-level: https://techcrunch.com/2016/12/06/aragos-ai-can-now-beat-some-human-players-at-complex-civ-strategy-games/ 
15. An introductory tutorial on the Internet of Things: http://www.kdnuggets.com/2016/12/internet-of-things-tutorial-chapter-1-introduction.html 
16. Many companies are still lacking the skills to implement machine learning projects: http://www.techrepublic.com/article/infographic-many-companies-lack-skills-to-implement-and-support-ai-and-machine-learning/ 
17. Resisting catastrophic forgetting in neural networks: http://www.theregister.co.uk/2016/12/06/catastrophic_forgetting/ 
18. Paper on resisting catastrophic forgetting: https://arxiv.org/abs/1612.00796
19. Microsoft is partnering with Cray to run deep neural networks on supercomputers: http://www.techrepublic.com/article/microsoft-partners-with-cray-to-run-deep-learning-algorithms-on-supercomputers/ 
20. Another basic overview of machine learning: http://www.kdnuggets.com/2016/12/too-afraid-ask-about-artificial-intelligence-machine-learning.html 
21. A neural network based "ahem" detector, used to clean-up podcasts: http://www.datasciencecentral.com/profiles/blogs/ahem-detector-with-deep-learning 
22. Google's DeepMind open sources more of its software: http://www.techrepublic.com/article/googles-deepmind-lab-opens-up-source-code-joins-race-to-develop-artificial-general-intelligence/ 
23. Another way deep learning is improving speech recognition: http://www.theregister.co.uk/2016/12/09/improving_computers_learning_speech/ 
24. 5 sources of bias in AI: https://techcrunch.com/2016/12/10/5-unexpected-sources-of-bias-in-artificial-intelligence/ 
25. Why we shouldn't let computers (and by extension AI) do our thinking for us: https://www.theguardian.com/technology/2016/dec/10/google-facebook-critical-thinking-computers
26. Using machine learning to search for trademarked logos: https://techcrunch.com/2016/12/12/trademarkvision-uses-machine-learning-to-make-finding-logos-as-easy-as-a-reverse-image-search/ 
27. An AI that helps marketers write: https://techcrunch.com/2016/12/12/atomic-ai-helps-marketers-write-better/ 
28. How to apply machine learning to business problems: http://techemergence.com/apply-machine-learning-to-business-problems/ 
29. Governmental challenges with AI: https://www.technologyreview.com/s/603036/the-government-isnt-doing-enough-to-solve-big-problems-with-ai/?utm_campaign=internal&utm_medium=homepage&utm_source=grid_1