Saturday, July 28, 2018

Watson IBM and Amazon AI solutions, pitfalls.



https://www.clarin.com/tecnologia/inteligencia-artificial-pifia-averguenza-ibm-amazon-producto-pedazo-mierda_0_H1W9godVQ.html

IBM’s Watson supercomputer recommended ‘unsafe and incorrect’ cancer treatments, internal documents show
https://www.statnews.com/2018/07/25/ibm-watson-recommended-unsafe-incorrect-treatments/

Amazon’s Face Recognition Falsely Matched 28 Members of Congress With Mugshots
https://www.aclunc.org/blog/amazon-s-face-recognition-falsely-matched-28-members-congress-mugshots


BIG HOAX,  Watson IBM
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/artificial-intelligence-can-watson-save.html
TC article: Facebook hired eHarmony’s chief scientist… but not for its new dating feature
https://onlinedatingsoundbarrier.blogspot.com/2018/05/tc-article-facebook-hired-eharmonys.html
Viola.AI .. but Match failed with Amazon Alexa
https://onlinedatingsoundbarrier.blogspot.com/2018/01/violaai-but-match-failed-with-amazon.html

http://www.onlinepersonalswatch.com/news/2018/01/match-pulls-its-alexa-skill-giving-controversial-dating-tips.html

and Chief Scientist At eHarmony Cavorts With The ... Facebook
http://onlinedatingsoundbarrier.blogspot.com.ar/2018/01/about-chief-scientist-at-eharmony.html
 
My bet: He is copycatting WATSON IBM, in same manner as Dr. Galen Buckwalter did (Soulmates.ai), but Buckwalter used the HEXACO model of personality (BIG FIVE, or OCEAN is obsolete now)

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
 

That is the only way to improve recommender systems, to include the personality traits of their users.
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/01/paper-comparative-study-of-people-to_14.html  
 

They need to calculate personality similarity between users but there are different formulas to calculate similarity.

In case you did not see, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates until now because they mostly use the Big Five model to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old.
 

The key to long-lasting romance: COMPATIBILITY is exactly STRICT PERSONALITY SIMILARITY and not "meet other people with similar interests or political views". 
 


Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena? 
The same approach to innovate in the Online Dating Industry == 16PF5 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns.
Online Dating sites have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 test instead and another method to calculate similarity.

High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.
Without offering the NORMATIVE 16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.

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