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Presentatie Nal Kalchbrenner

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Presentatie van het Datacongres ''data science voor maatschappelijke uitdagingen'' op 22 november 2018

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Presentatie Nal Kalchbrenner

  1. 1. The Deep Learning Shift: Past, Present and near Future Nal Kalchbrenner
  2. 2. 2012 Machines learn to “see”
  3. 3. ImageNet Challenge
  4. 4. ImageNet Challenge
  5. 5. ImageNet Challenge
  6. 6. 2013-2015 Machines learn to “translate”
  7. 7. Neural Machine Translation
  8. 8. Neural Machine Translation
  9. 9. Neural Machine Translation
  10. 10. 2015-2016 Machines learn to “play Go”
  11. 11. AlphaGo
  12. 12. AlphaGo
  13. 13. AlphaGo 280 million viewers
  14. 14. What made these possible?
  15. 15. New Computing Hardware and Increased Capacity
  16. 16. Open Academic & Industrial Research Open sourcing models, code and datasets both in industry and in academia (Google AI/Brain, Microsoft, FAIR, OpenAI, etc) Strong ties between academia and industry
  17. 17. Google AI & Brain locations 500+ Research Scientists and Research Engineers in ~10 locations only in Brain
  18. 18. Location of lab
  19. 19. Our research focus “Hi, how goes it?” “Hallo, wie geht’s?”
  20. 20. What’s coming up next?
  21. 21. Machine Learning in Health
  22. 22. Machine Learning in Health Healthy Diseased Hemorrhages No DR Mild DR Moderate DR Severe DR Proliferativ e DR
  23. 23. Self-Driving Cars
  24. 24. Exciting times! Thanks!

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