Review for 20 March 2017

Below are some of the interesting links I Tweeted about recently.

1. We will get closer to AIs, but I think we will go thru many iterations of wearables before we get to implants: https://techcrunch.com/2017/02/13/elon-musk-reiterates-the-need-for-brain-computer-interfaces-in-the-age-of-ai/
2. Overview of 23 different types of regression: http://www.datasciencecentral.com/profiles/blogs/23-types-of-regression 
3. While AI is a convenient catch-all term, machine learning, AI, ANN, are really different things: http://www.datasciencecentral.com/profiles/blogs/difference-between-machine-learning-data-science-ai-deep-learning 
4. Possibly an application of deep learning ANN? Nest cameras can now recognise doors and when people enter view: http://www.theverge.com/2017/2/14/14609310/nest-cam-door-recognition-alerts-feature 
5. Not sure what, if any, AI is present here, but better customer service is probably useful: https://techcrunch.com/2017/02/13/salesforce-brings-ai-to-service-cloud/ 
6. I just examined a Ph.D. thesis doing earthquake prediction with machine learning-still a long way to go: https://www.scientificamerican.com/article/can-artificial-intelligence-predict-earthquakes/
7. Like I tell my IT students: If you lose data because you don't have a backup, it's your fault: https://www.insidehighered.com/blogs/gradhacker/necessity-dedicated-backup-system
8. I know the feeling, I returned to NZ from AU-there's no place like home: https://www.linkedin.com/pulse/why-i-moved-back-india-after-10-years-usa-nupur-dave?trk=eml-email_feed_ecosystem_digest_01-hero-0-null&midToken=AQHOB1JUwrXpFw&fromEmail=fromEmail&ut=3BwiP8uTD-wDE1
9. Some free introductory ebooks on machine learning and other data processing topics: http://www.littlebeelibrary.com
10. A simple Python introduction to k-means clustering: http://www.kdnuggets.com/2017/03/k-means-clustering-algorithms-intro-python.html 
11. Uses of AI in education: https://www.techemergence.com/examples-of-artificial-intelligence-in-education/  Educational data mining is another big area of research
12. So important to do this - ridding your data of bias: http://computerworld.com/article/3163145/data-analytics/how-to-root-out-bias-in-your-data.html
13. Feedspot has added my computational intelligence blog http://computational-intelligence.blogspot.com  to their list of top 50 blogs on AI: http://blog.feedspot.com/ai_blogs
14. General business applications of AI: http://www.datasciencecentral.com/profiles/blogs/how-to-put-ai-to-work 
15. Best R packages for importing and processing data: http://computerworld.com/article/2921176/business-intelligence/great-r-packages-for-data-import-wrangling-visualization.html 
16. The impact of deep learning on SEO: http://www.datasciencecentral.com/profiles/blogs/will-deep-learning-change-the-digital-marketing-game 
17. The problems with interpreting deep learning models: https://www.datanami.com/2017/03/15/scrutinizing-inscrutability-deep-learning/ 
18. Play a musical duet with a deep neural network: https://techcrunch.com/2017/02/16/googles-a-i-duet-experiment-lets-you-jam-with-the-machine/ 
19. Using machine learning to recognise items in movies, so people can buy them: https://techcrunch.com/2017/02/13/working-with-major-studios-thetake-launches-ai-image-recognition-engine-for-businesses/ 
20. Specialised deep learning chips for consumer hardware: http://spectrum.ieee.org/tech-talk/semiconductors/processors/to-get-ai-in-everyday-gadgets-engineers-go-to-specialized-hardware 
21. I suspect that the proportion of psycopaths in senior academic positions is also higher than the general population: https://www.theguardian.com/technology/2017/mar/15/silicon-valley-psychopath-ceo-sxsw-panel