A co-presentation to the New York Taiwanese Finance Association on select topics within Big Data, Deep Learning, and the New Roles of Cognitive Systems in society

1. March 22, 2016
Big Data, Deep Learning, and New Roles of
Cognitive Systems in Human World
Erin M. Burke, J.D., M.S.
D. Frank Hsu, Ph.D.

2. Evolution of AI in
Chess
Mariano Kamp, Creative Commons Attribution License

3. 1985 1989
Chiptest (Carnegie Mellon)
50,000 moves/sec
Chiptest-M
500,000 moves/sec
Wins first
world
championship,
Kasparov
easily defeats
1987 1988
Deep Thought 0.01, 0.02
720,000 moves/sec

4. 1990 1993
Move to
Yorktown
Heights,
2MM
positions/second
, increased
efforts on parallel
search algorithm
Renamed
Deep Blue
1991
Increased
processing
power, 6-7MM
positions per
second, “Deep
Thought II”, ACM
World Champ Defeats
Kasparov,
100MM
positions/second
1997

5. Deep Blue Choices
❖ Evaluation algorithm measures
the "goodness" of a given chess
position:
❖ material
❖ position
❖ King safety
❖ tempo
❖ Selective Searching
❖ Pruning, not brute force
❖ Parallel computing
James Gardner, Creative Commons
Attribution License

6. Deep Blue v.
Watson
Different technologies,
different skills. Sheer
computing v. cognition.

7. –Stephen Baker, author of “Final Jeopardy”
“Watson is a far more sophisticated program than
Deep Blue, because it's closer to mastering
kindergarten (though still far away)”

8. Big Data 4 Vs
❖ Volume
❖ Variety
❖ Velocity
❖ Veracity

9. Deep Learning
❖ Train Artificial Neural Networks on Big Data - audio,
pictures,
❖ ANN: learning and reinforcement
❖ Clustering
❖ Examine Enormous number of examples-> not hand-
coded rules based (better on GPUs)
❖ Layers of algorithms, themselves discovered by sheer
processing power

10. Wikimedia Commons

11. Alphago
❖ GO: self-ignorance-> knowing more than we can tell is
difficult to program. Needs to “learn on its own”, and
therefore use “deep learning”.
❖ Difference with chess:
❖ Too many choices for even the fastest computers
❖ Difficult to assess where to start
❖ Fed millions of examples “learning” and then played
against itself to learn more “reinforcement”

12. Applications
❖ Speech recognition
❖ credit card fraud detection
❖ radiology
❖ finance: temporal signals - 3D view of trends, patterns
across different time scales

13. Fuzzy Logic Application
E-mailing
Students
Goal: Use correct tone in
email to students
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