Saturday, April 2, 2016

Weekly Review 1 April 2016

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

  1. Valuing the AI market for 2016
  2. Using machine learning to improve automatic speech recognition:
  3. Resistive Processing Units to accelerate training in deep learning neural networks:,31484.html
  4. Paper on Resistive Processing Units for deep learning:
  5. Computers don't cause a net decrease in job numbers, but do increase inequality, with the lowest-paid hit hardest:
  6. What I like to call "avoiding work by doing work" - doing small tasks to avoid doing larger tasks: 
  7. UK's Wellcome Trust wants research they fund published in open access journals: 
  8. Robots learning to pick things up using deep learning neural networks: 
  9. This article seems to be arguing that it's better to get "off the shelf" machine learning than to develop your own: 
  10. AlphaGo and the declining advantage of big companies: 
  11. Lots of companies getting into AI now:
  12. AI hits the mainstream:
  13. AI is getting big in Silicon Valley: 
  14. Note to post-grads: don't EVER use graphs like these in your dissertation, I will fail you! 
  15. Neural network chip could bring convolutional neural networks to mobile devices: 
  16. One step to become a machine learning expert: 
  17. Building models is a skill, and like every other skill it must be practiced to be mastered: 
  18. How to tell if the performance of two classifiers is statistically significantly different:
  19. The fortunate failure of Microsoft's Tay: 
  20. Some people would rather have a computer for a boss than a human:
  21. Is the next step for Google DeepMind playing poker? 
  22. Machine learning in signature detection for cybersecurity: 
  23. Google hypes machine learning to sell its cloud computing platform: 
  24. I'm sure I read / reviewed a paper about this - density-based unsupervised clustering: 
  25. Fighting China's - and especially Beijing's - smog with machine learning:
  26. Low-power, neuromorphic chips being applied in the US nuclear industry: 
  27. Machine learning in signature detection for cybersecurity part 2: 
  28. How Google plans to solve Artificial General Intelligence: 
  29. Avoiding complexity in machine learning: 
  30. Artificial Intelligence still works best when AI is paired with humans:
  31. Would the health care app space be a good place to apply machine learning? 
  32. How Baidu is using AI, especially deep learning: 
  33. I wonder if this approach could be used to generate real estate listings? They're not that different from clickbait:


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