Weekly Review 27 May 2016

Some interesting links that I Tweeted about in the last week:

1. AI and the rise of the "useless" class: https://www.theguardian.com/technology/2016/may/20/silicon-assassins-condemn-humans-life-useless-artificial-intelligence
2. Overview of the applications of IBM's Watson: http://www.extremetech.com/extreme/228877-ibm-watson-amps-up-moogfest-2016-with-ai-infused-programming
3. Machine learning is the "automation of automation": http://www.kdnuggets.com/2016/05/explain-machine-learning-software-engineer.html
4. The promise of Google's AI: https://www.theguardian.com/technology/2016/may/20/google-ai-machine-learning-skynet-technology
5. Google Home means holding conversations with computers - will they use those conversations to make better AI? https://www.technologyreview.com/s/601530/google-thinks-youre-ready-to-converse-with-computers/
6. A knowledge of measurement theory is really important: http://www.kdnuggets.com/2016/05/dont-just-assume-data-interval-scale.html See also here: http://computational-intelligence.blogspot.co.nz/2015/03/measurement-theory.html 
7. China is really going in the wrong direction now. A real shame, I know lots of good people among China's academia: http://www.theguardian.com/world/2016/may/24/academics-china-crackdown-forces-intellectuals-abroad
8. Australian robot livestock workers: https://www.newscientist.com/article/2089321-robot-ranchers-monitor-animals-on-giant-australian-farms/?utm_source=NSNS&utm_medium=ILC&utm_campaign=webpush&cmpid=ILC%257CNSNS%257C2016-GLOBAL-webpush-ROBOTRANCHERS
9. Google is trying to teach an AI to be artistic: http://www.theverge.com/2016/5/23/11743948/google-artificial-intelligence-magenta-art-music-project
10. The (potential) contribution of AI to medicine: http://www.extremetech.com/extreme/228830-the-next-major-advance-in-medicine-will-be-the-use-of-ai
11. Some thoughts on language choice for writing a web crawler: http://www.bigdatanews.com/profiles/blogs/which-language-is-better-for-writing-a-web-crawler-php-python-or Last crawler I wrote was in Python.
12. Natural language processing and AI in Facebook: http://www.techrepublic.com/article/why-facebook-wants-to-use-ai-to-track-your-conversations-online/
13. Facebook is planning on using neural networks for translation: https://www.technologyreview.com/s/601562/facebook-plans-to-boost-its-translations-using-neural-networks-this-year/ That'll need some really, really big neural networks.
14. What's good and what's bad about TensorFlow: http://www.kdnuggets.com/2016/05/good-bad-ugly-tensorflow.html
15. The disappointment of AI personalisation: http://www.techrepublic.com/article/big-datas-big-disappointment-why-ai-personalization-is-pathetic/
16. More than just bots in the intelligent application ecosystem: http://techcrunch.com/2016/05/24/the-intelligent-app-ecosystem-is-more-than-just-bots/
17. Machine learning algorithms that learn from fewer examples: https://www.technologyreview.com/s/601551/algorithms-that-learn-with-less-data-could-expand-ais-power/
18. Biased data will give you biased models: http://theinstitute.ieee.org/ieee-roundup/opinions/ieee-roundup/bias-in-code-is-a-problem-that-cannot-be-ignored- I used to teach this to my third-year AI class, why don't pros know?
19. Why Facebook's AI can't recognise a mirror selfie: http://motherboard.vice.com/en_au/read/why-artificial-intelligence-cant-detect-mirror-selfies
20. Terrapattern is a reverse image searching on maps, powered by a convolutional neural network: http://techcrunch.com/2016/05/25/terrapattern-is-a-neural-net-powered-reverse-image-search-for-maps/
21. A biased data set will give a biased model, even if the biases are racial/gender/cultural. Why is this still news? http://motherboard.vice.com/en_au/read/weve-already-taught-artificial-intelligence-to-be-racist-sexist
22. At least the US government is taking AI seriously. Will others? http://www.geekwire.com/2016/white-house-ai-workshop-focuses-machines-plus-humans-will-affect-government/
23. Why Python is such a good match for machine learning: http://www.analyticbridge.com/profiles/blogs/machine-learning-with-python-why-do-they-form-the-best 
24. Something of a glossary of key machine learning terms: http://www.kdnuggets.com/2016/05/machine-learning-key-terms-explained.html
25. Amazon is expanding its cloud-based machine learning offerings: http://www.bloomberg.com/news/articles/2016-05-26/amazon-to-battle-google-with-new-cloud-service-for-ai-software