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Grace Hopper Conference Opening Keynote

See the video here: http://gracehopper.anitaborg.org/conference-overview/livestream-schedule-2015/wednesday-livestream-2015/

My GHC keynote covers the state of technology in Machine Intelligence, and also what it means to have a career as a computer scientist in a field where the technology and the products are evolving so quickly.

(I use a presentation style with lots of images and very little content in the slides, and this presentation was not designed to stand alone.)

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Grace Hopper Conference Opening Keynote

  1. Machine Intelligence: A Startup Adventure Hilary Mason @hmason
  2. Good morning!
  3. Technology is changing.
  4. (and people stay the same)
  5. Machine Intelligence.
  6. By Gene Kogan, based on the paper by Gatys, Ecker, Bethge.
  7. @pentametron
  8. Data products are everywhere.
  9. (it’s boring)
  10. Rules- based Creative Repetitive
  11. Why now?
  12. Affordable computation.
  13. Algorithms.
  14. Data!!
  15. And we are just at the beginning!
  16. [robot dog?]
  17. None of this is entirely new.
  18. [slides to come]
  19. What it means to be a Computer Scientist is changing.
  20. math & stats code communication nerds nerds nerds awesome nerds! Data science:
  21. Predicting the future is hard.
  22. Where does innovation come from?
  23. Academia
  24. Enterprise!
  25. Startups.
  26. The System is Complex.
  27. you
  28. you
  29. Creating an organization is just deploying a different kind of infrastructure.
  30. We focus on innovation opportunities through data and algorithms.
  31. Academic Research Startups Established Companies
  32. The biggest opportunities might surprise you.
  33. What makes a machine intelligence technology ‘interesting’?
  34. 1) a theoretical breakthrough
  35. 2) a change in economics http://www.mkomo.com/cost-per-gigabyte
  36. 3) a capability becomes a commodity
  37. WTF??
  38. 4) new data is available
  39. 4b) data is made useful
  40. We create reports and prototypes around each emerging capability, and give advice.
  41. papers + prototypes “nerd friends” growth
  42. Working with a broad set of companies leads us to generally appealing applications.
  43. Efficient models for learning from streams of data as they are generated.
  44. pictograph.us
  45. [caution]
  46. What’s next?
  47. You’re building the future. Please build the one you want to live in. ¯_(ツ)_/¯
  48. I’m Hilary. @hmason. hilary@fastforwardlabs.com Thank you!!
  49. Photo & Project Credits • NASA’s Marshall Space Flight Center, http://luvit.me/1Oown6H • Pentametron, by Ranjit Bhatnagar, https://twitter.com/pentametron • StyleNet paper by Gatys, Ecker, Bethge http://arxiv.org/abs/1508.06576 • Hand on smartphone, www.japanexperterna.se/?attachment_id=3068 • Sunflower by Raffaele Camardella, http://luvit.me/1LISN1T • Magic Rabbit by Jenn and Tony Bot, http://upvot.es/1MnLp6u • ProPublica Surgeon Scorecard, https://projects.propublica.org/surgeons/ • Google Deep Dream, https://github.com/google/deepdream

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