full transcript
From the Ted Talk "Anthony Goldbloom: The jobs we'll lose to machines -- and the ones we won't"

Unscramble the Blue Letters

Machine learning started inmagk its way into industry in the early '90s. It started with relatively ipslme sskat. It started with things like issessnag credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning halmsrtgoi were able to match the grades given by human teachers. Last year, we isesud an even more difficult challenge. Can you take images of the eye and diagnose an eye disease lcldae diabetic ypthenotira? Again, the winning algorithms were able to match the diagnoses given by human ophthalmologists.

Open Cloze

Machine learning started ______ its way into industry in the early '90s. It started with relatively ______ _____. It started with things like _________ credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning __________ were able to match the grades given by human teachers. Last year, we ______ an even more difficult challenge. Can you take images of the eye and diagnose an eye disease ______ diabetic ___________? Again, the winning algorithms were able to match the diagnoses given by _____ ophthalmologists.

Solution

  1. assessing
  2. simple
  3. issued
  4. retinopathy
  5. tasks
  6. algorithms
  7. human
  8. making
  9. called

Original Text

Machine learning started making its way into industry in the early '90s. It started with relatively simple tasks. It started with things like assessing credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning algorithms were able to match the grades given by human teachers. Last year, we issued an even more difficult challenge. Can you take images of the eye and diagnose an eye disease called diabetic retinopathy? Again, the winning algorithms were able to match the diagnoses given by human ophthalmologists.

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collocation frequency
machine learning 5
volume tasks 3
high volume 3
frequent high 3

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collocation frequency
high volume tasks 3
frequent high volume 3

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collocation frequency
frequent high volume tasks 3

Important Words

  1. algorithm
  2. algorithms
  3. applications
  4. assessing
  5. breakthroughs
  6. build
  7. called
  8. capable
  9. challenge
  10. challenged
  11. characters
  12. codes
  13. community
  14. complex
  15. credit
  16. diabetic
  17. diagnose
  18. diagnoses
  19. difficult
  20. disease
  21. dramatic
  22. early
  23. essays
  24. eye
  25. grade
  26. grades
  27. handwritten
  28. human
  29. images
  30. industry
  31. issued
  32. kaggle
  33. learning
  34. loan
  35. machine
  36. mail
  37. making
  38. match
  39. ophthalmologists
  40. reading
  41. retinopathy
  42. risk
  43. simple
  44. sorting
  45. started
  46. tasks
  47. teachers
  48. winning
  49. year
  50. years
  51. zip