Monday, August 8, 2016

Weekly Review 8 August 2016

It's been a while since my last review post. This is because I have been away at the ITx conference in Wellington, followed by the WCCI 2016 conference in Vancouver, B.C. Below are some of the interesting links I Tweeted about in the last few weeks.

  1. A more and more common story, this is why I went into the private tertiary education sector, better job security:
  2. An overview of Bayesian machine learning:
  3. An AI-based VC fund:
  4. An improved Turing Test shows how dumb chatbots really are:
  5. A tutorial on machine learning in Python:
  6. An AI that detects hints of depression in speech:
  7. The kinds of problems that AI still can't do:
  8. How machine learning is driving artificial intelligence:
  9. Five open-source deep learning projects:
  10. The coming clash between EU regulations and artificial intelligence:
  11. How AI-driven companies like Google depend on public data:
  12. The problems with current chatbots:
  13. The application of supercomputers in deep learning:
  14. is launching an AI executive assistant:
  15. A list of resources for learning about deep learning:
  16. A machine learning based email autoresponder:
  17. Predicting Game of Thrones betrayals using machine learning:
  18. Ten categories for machine learning and AI algorithms:
  19. Helping AI better understand what we are saying to them:
  20. The AI boom in Silicon Valley:
  21. Good news, 9 mill. people will be liberated from sweatshops by robots-Bad news, 9 mill. people without jobs:
  22. Google's using deep learning to optimise the energy efficiency of cooling its server farms:
  23. A list of more than 50 machine learning API:
  24. How deep learning networks scale:
  25. Using machine learning to manage virtual servers:
  26. Google, Microsoft, IBM, Amazon, Facebook are all renting-out access to their AI systems:
  27. Current developments in deep learning:
  28. Yes, AI is just as biased as people, because AI are made by people. That has been obvious for a long time:
  29. Diagnosing autism using machine learning:
  30. Why Open Source programming languages are winning over proprietary languages: Better to learn R than Matlab?
  31. An overview of deep learning neural networks applied to machine translation:
  32. A commented list of resources explaining NoSQL:
  33. A new version of PMML - Predictive Modelling Markup Language - has been released: 
  34. Ten simple rules for using statistics properly and effectively:
  35. How to use machine learning for face recognition:
  36. Using machine learning to predict the genetic basis of autism:
  37. Why Harvard Business School is teaching its MBA students about AI:
  38. Two more Google machine learning API are now in open beta:
  39. Top programming languages for 2016 - Python & R are now numbers 3 & 5, respectively.
  40. Detecting sarcasm using a neural network: A lot of people still struggle to detect sarcasm...
  41. Developing chatbots for HR: 
  42. Will artificial intelligence's ever get common sense?
  43. How investors feel about artificial intelligence:
  44. Intelligent security and surveillance systems:
  45. OpenAI is calling for an "AI Police" - I seem to remember the "Turing Police" in Neuromancer...
  46. Using machine learning to predict crop-yield from satellite images: 
  47. IBM is arguing that AI should be assisting people rather than replacing them:
  48. Arthur C. Clarke was writing about IA - Intelligence Amplifiers - in 1986:
  49. Using machine learning to find zero-day exploits on the dark web:
  50. Yahoo has used machine learning to develop a troll-detecting algorithm:
  51. The paper describing Yahoo's troll-detector:
  52. A paper on estimating crop yield from images, this time in China:

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