Friday, April 8, 2016

Weekly Review 8 April 2016

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

  1. Assisting dieting with machine learning: http://spectrum.ieee.org/the-human-os/biomedical/diagnostics/machine-learning-for-easier-dieting
  2. Microsoft is open sourcing their chatbot software: http://www.theguardian.com/technology/2016/mar/31/now-anyone-can-build-own-version-microsoft-racist-sexist-chatbot-tay
  3. Using deep learning to search Shutterstock's image collection: http://www.kdnuggets.com/2016/04/shutterstock-deep-learning-change-language-search.html
  4. Being an academic is hard. Becoming one is harder. So much of an academic career is a test of endurance. http://muckyphd.blogspot.co.nz/2016/03/coming-to-terms-with-academic-failure.html 
  5. The Cyc project is still going - and finding applications in medicine: http://techemergence.com/a-30-year-old-ai-project-hits-the-market/ 
  6. Microsoft launches Cognitive Services http://venturebeat.com/2016/03/30/microsoft-cognitive-services-project-oxford/  22 APIs on computer vision, speaker recognition, etc: https://www.microsoft.com/cognitive-services 
  7. On the exploitation in academic publishing: https://medium.com/age-of-awareness/academic-publishing-is-a-goddamned-exploitative-farce-75930d3ce3d0#.95kkkly94
  8. C4.5, SVM & APRIORI algorithms explained: http://dataconomy.com/top-3-algorithms-plain-english/
  9. Dieting and machine learning: http://motherboard.vice.com/en_au/read/how-machine-learning-dieting-app-health 
  10. How to make AIs sound more like humans: http://www.computerworld.com/article/3051174/big-data/what-will-it-take-to-make-ai-sound-more-human.html
  11. Combining human experts with machine learning for cybersecurity: http://www.techrepublic.com/article/how-one-ai-security-system-combines-humans-and-machine-learning-to-detect-cyberthreats/
  12. Google's machine learning for developers: http://www.techrepublic.com/article/how-developers-can-take-advantage-of-machine-learning-on-google-cloud-platform/
  13. The job market for new PhDs is getting smaller and smaller: https://www.insidehighered.com/news/2016/04/04/new-data-show-tightening-phd-job-market-across-disciplines
  14. AI systems in journalism, now getting as good as human writers: http://www.theguardian.com/media/2016/apr/03/artificla-intelligence-robot-reporter-pulitzer-prize 
  15. Deep learning for smart cities: http://www.datasciencecentral.com/profiles/blogs/deep-learning-applications-for-smart-cities 
  16. Some machine learning "trade secrets" http://www.datasciencecentral.com/profiles/blogs/machine-learning-few-rarely-shared-trade-secrets 
  17. My h-index just hit 16 - will it stay there this time? https://scholar.google.com/citations?user=Z29KBKYAAAAJ 
  18. The applications of AI in finance: http://techemergence.com/dont-fear-ai-in-finance/ 
  19. Facebook's AI for automatically describing images: http://www.techrepublic.com/article/facebook-is-using-ai-to-help-blind-people-see-the-photos-in-their-newsfeed/ 
  20. Teaching experience is important for post-grads. Co-teaching is one approach to getting it: https://www.insidehighered.com/advice/2016/04/05/advantages-co-teaching-graduate-students-essay 
  21. Microsoft announces its Cognitive Services and Bot Framework: https://blogs.technet.microsoft.com/machinelearning/2016/03/30/from-analytical-applications-to-intelligent-solutions/ 
  22. Nvidia launches a 15-billion transistor chip for deep learning: http://venturebeat.com/2016/04/05/nvidia-creates-a-15b-transistor-chip-for-deep-learning/ 
  23. Another article on Nvidia's 15 billion transistor chip for deep learning: https://www.technologyreview.com/s/601195/a-2-billion-chip-to-accelerate-artificial-intelligence/#/set/id/601193/ 
  24. How Livermore National Laboratory will test IBM's neuromorphic chips: http://spectrum.ieee.org/tech-talk/computing/hardware/how-livermore-scientists-will-put-ibms-brain-inspired-chips-to-the-test 
  25. Applying deep learning to the Internet of Things using H20: http://www.kdnuggets.com/2016/04/deep-learning-iot-h2o.html
  26. Some tips and tricks for using deep neural networks: http://www.datasciencecentral.com/profiles/blogs/must-know-tips-tricks-in-deep-neural-networks 
  27. AI in the military: http://www.techrepublic.com/article/how-ai-powered-robots-will-protect-the-networked-soldier/
  28. Machine learning in business revenue forecasting: http://www.datasciencecentral.com/profiles/blogs/what-s-a-cfo-s-biggest-fear-and-how-can-machine-learning-help 
  29. The basics of GPU computing: http://www.kdnuggets.com/2016/04/basics-gpu-computing-data-scientists.html 
  30. A description of deep learning stochastic depth networks: http://www.kdnuggets.com/2016/04/stochastic-depth-networks-accelerate-deep-learning.html