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Critique of 2018 Turing Award for Drs. Bengio & Hinton & LeCun


Conclusion (~1,700 words).
All backed up by over 200 references (~6,500 words).
We must stop crediting the wrong people for inventions made by others.
Instead let s heed the recent call in the journal
Nature:
Let 2020 be the year in which we value those who ensure that
science is self-correcting [SV20].
Like those who know me can testify, finding and citing original sources of scientific and technological innovations is important to me, whether they are mine or other people s [DL1][DL2][HIN][NASC1-9]. The present page is offered as a resource for computer scientists who share this inclination.
By grounding research in its true intellectual foundations and crediting the original inventors, ....

United States , Holland Library , New York , United Kingdom , British Columbia , Mountain View , San Diego , San Francisco , World University , Noord Holland , Andhra Pradesh , Baden Wüberg , Eteläuomen Läi , Brighton And Hove , University Of Colorado At Boulder , City Of , Comunidad Autonoma De Cataluna , Long Beach , Systemei Monatshefte , Technische Universit , Ivakhnenko Lapa , Sherrington Kirkpatrick , Terrence Sejnowski , Birkhaeuser Basel , Principia Mathematica , Konrad Zuse ,

Algorithm helps artificial intelligence systems dodge "adversarial" inputs | MIT News | Massachusetts Institute of Technology


Caption:
A deep-learning algorithm developed by MIT researchers is designed to help machines navigate in the real world. In tests with the video game Pong, the researchers introduced an “adversary” that pulled the ball slightly further down than it actually was.
Credits:
Image: Jose-Luis Olivares, MIT
Terms of Use:
Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a
Creative Commons Attribution Non-Commercial No Derivatives license.
You may not alter the images provided, other than to crop them to size. A credit line must be used when reproducing images; if one is not provided ....

Michael Everett , Ford Motor Company , Department Of Aeronautics , Transactions On Neural Networks , Certified Adversarial Robustness , Deep Reinforcement , Neural Networks , Astro Professor Jonathan , Jonathan How , Bjorn Lutjens , Mit Aeroastro , Deep Reinforcement Learning , Adversarial Attacks , Autonomous Vehicle Navigation , Collision Avoidance , மைக்கேல் எவரெட் , ஃபோர்ட் மோட்டார் நிறுவனம் , துறை ஆஃப் வான்செலவுத்துறை , பரிவர்த்தனைகள் ஆன் நரம்பியல் நெட்வொர்க்குகள் , ஆழமான வலுவூட்டல் , நரம்பியல் நெட்வொர்க்குகள் , ஆஸ்ட்ரோ ப்ரொஃபெஸர் ஜொனாதன் , ஜொனாதன் எப்படி , ஆழமான வலுவூட்டல் கற்றல் , தன்னாட்சி வாகனம் வழிசெலுத்தல் ,