Saturday, May 14, 2016

Weekly Review 13 May 2016

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

  1. DeepMind claims is has good privacy protection so should be trusted with data on millions of patient records: https://www.theguardian.com/technology/2016/may/06/deepmind-best-privacy-infrastructure-handling-nhs-data-says-co-founder
  2. I suspect my daughter's generation will be the last to pay their way through university by flipping burgers: http://www.techrepublic.com/article/ai-will-destroy-entry-level-jobs-but-lead-to-a-basic-income-for-all/
  3. I liked to implement algorithms myself when I was a post-grad: http://www.kdnuggets.com/2016/05/implement-machine-learning-algorithms-scratch.html Don't have time to do that kind of thing now.
  4. Facebook is building an AI that builds AIs: http://www.wired.com/2016/05/facebook-trying-create-ai-can-create-ai/
  5. Is "genetics-inspired multi-AI approach" a fancy name for an evolutionary algorithm? http://www.theregister.co.uk/2016/05/06/ebay_buys_expertmaker/
  6. Predicting the winners of horse races with swarm intelligence: http://www.techrepublic.com/article/swarm-ai-predicts-the-2016-kentucky-derby/
  7. Machine learning for personal stylists: http://www.computerworld.com/article/3067264/artificial-intelligence/at-stitch-fix-data-scientists-and-ai-become-personal-stylists.html
  8. Machine learning in marketing: http://www.martechadvisor.com/articles/mobile-app-dev-marketing/marketing-in-a-digital-world-machine-learning-is-upping-innovation-and-agility/
  9. Why AI is going to disappear, become invisible: http://techcrunch.com/2016/05/07/the-next-ai-is-no-ai/
  10. An AI for a teaching assistant: http://www.wsj.com/articles/if-your-teacher-sounds-like-a-robot-you-might-be-on-to-something-1462546621
  11. Preparing a business to include AI: http://www.techrepublic.com/article/how-to-prepare-your-business-to-include-ai/
  12. Why we may need an ethics framework for AI: http://www.theguardian.com/commentisfree/2016/may/08/the-guardian-view-on-artificial-intelligence-look-out-its-ahead-of-you
  13. Using machine learning to suggest citations for your research writing: http://techcrunch.com/2016/05/08/helix-conducts-research-as-you-write/
  14. Categorising the importance of messages using machine learning: http://techcrunch.com/2016/05/08/deep-focus-saves-you-from-being-inundated-by-unimportant-messages/
  15. How open source projects are moving machine learning forwards: https://www.linux.com/news/open-source-projects-are-transforming-machine-learning-and-ai
  16. Ambient intelligence - AI everywhere: http://techcrunch.com/2016/05/07/the-next-stop-on-the-road-to-revolution-is-ambient-intelligence/
  17. Proof-reading. It's really, really important. Of all the words they could mis-spell... https://www.insidehighered.com/quicktakes/2016/05/09/unfortunate-typo-tcu-commencement-program
  18. Open Network Insight uses machine learning for network security: http://www.datanami.com/2016/05/09/oni-may-best-hope-cyber-security-now/
  19. Deep learning in Python with the Keras library: http://machinelearningmastery.com/introduction-python-deep-learning-library-keras/
  20. Interpreting radiological images with machine learning: http://techcrunch.com/2016/05/09/behold-ai-launches-artificially-intelligent-medical-software-to-find-abnormalities-faster/ IIRC David Fogel did this kind of thing around 1993.
  21. Some pros and cons of chatbots: http://www.kdnuggets.com/2016/05/ai-chatbots-when-if.html
  22. Facebook's FBLearner Flow machine learning platform: http://venturebeat.com/2016/05/09/facebook-details-its-company-wide-machine-learning-platform-fblearner-flow/
  23. Using logistic regression and maximum entropy in Python: http://ataspinar.com/2016/05/07/regression-logistic-regression-and-maximum-entropy-part-2-code-examples/
  24. A machine learning based stock trading app: https://www.techinasia.com/8-securities-stock-trading-virtual-broker
  25. How to install and run TensorFlow on a Windows machine: http://www.netinstructions.com/how-to-install-and-run-tensorflow-on-a-windows-pc/
  26. The coming disruption from intelligent bots: http://www.forbes.com/sites/moorinsights/2016/05/05/rise-of-the-machines-part-2-artificial-intelligence-and-bots-promise-to-disrupt/#15ea457a7082
  27. How to become a good machine learning engineer: https://www.quora.com/How-can-one-become-a-good-machine-learning-engineer/answer/Nikhil-Dandekar
  28. A bit of context for AI: What humans need to learn about machine learning: http://www.computerworld.com/article/3067924/artificial-intelligence/what-humans-need-to-learn-about-machine-learning.html
  29. It's not coding, it's understanding the problem and designing a solution that's important: http://techcrunch.com/2016/05/10/please-dont-learn-to-code/
  30. Three skills every developer needs, according to Joel Spolsky: http://www.techrepublic.com/article/joel-spolsky-the-three-skills-every-software-developer-should-learn/
  31. Deep learning is definitely going to kill off jobs: http://www.techrepublic.com/article/ai-pioneer-ai-will-definitely-kill-jobs-but-thats-ok/
  32. IBM's Watson is being applied to cyber-security: http://www.techrepublic.com/article/ibm-watson-takes-on-cybercrime-with-new-cloud-based-cybersecurity-technology/
  33. Data mining can produce racist results, if the data being mined is influenced by racist policies: http://www.computerworld.com/article/3068622/internet/amazon-prime-and-the-racist-algorithms.html
  34. How AI is helping lawyers: http://www.fastcompany.com/3059725/how-ai-and-crowdsourcing-are-remaking-the-legal-profession
  35. Future trends in machine learning: http://www.geekwire.com/2016/future-machine-learning-5-trends-watch-around-algorithms-cloud-iot-big-data/
  36. Amazon has open-sourced it's deep learning software: http://venturebeat.com/2016/05/11/amazon-open-sources-its-own-deep-learning-software-dsstne/ Said to be 2x speed of TensorFlow: http://siliconangle.com/blog/2016/05/11/amazon-says-its-new-deep-learning-library-is-2x-faster-than-googles/
  37. Is the pressure to publish more papers, driving down the quality of those papers? http://www.nature.com/news/the-pressure-to-publish-pushes-down-quality-1.19887
  38. How long before we see deep learning on a quantum computer? Training ANN is a multi-parameter optimisation problem http://www.gizmag.com/quantum-computer-processor-walk-algorithm/43263/
  39. On the creativity of deep learning neural networks: http://www.kdnuggets.com/2016/05/deep-neural-networks-creative-deep-learning-art.html
  40. Why machine learning and python go together so well: http://www.analyticbridge.com/profiles/blogs/machine-learning-with-python-why-do-they-form-the-best
  41. The current state of neuromorphic chips: http://www.kdnuggets.com/2016/05/deep-learning-neuromorphic-chips.html
  42. Overview of Markov chains: http://www.analyticbridge.com/profiles/blogs/making-data-science-accessible-markov-chains
  43. Neural networks in JavaScript: http://www.kdnuggets.com/2016/05/implementing-neural-networks-javascript.html
  44. Why AI is the most important technology of today: http://techemergence.com/why-is-ai-todays-most-important-technology/
  45. The uses of AI in the enterprise: http://techcrunch.com/2016/05/12/clarifying-the-uses-of-artificial-intelligence-in-the-enterprise/
  46. Google has open-sourced their natural-language processing toolbox: http://siliconangle.com/blog/2016/05/12/meet-parsey-mcparseface-googles-new-open-source-language-understanding-tool/ Best. Name. Ever!
  47. Apple and Google competing in the mobile machine learning area: http://memeburn.com/2016/05/apple-googles-mobile-machine-learning-race/