“Why deep learning is suddenly changing your life” By Roger Rarloff
I am reading this article on Fortune. Some quotes with my thoughts:
Most scientists still prefer to call "deep learning" by their original academic designation: deep neural networks.
Neural nets aren't new. The concept dates back to the 1950s, and many of the key algorithmic breakthroughs occurred in the 1980s and 1990s. What's changed is that today computer scientists have finally harnessed both the vast computational power and the enormous storehouses of data.
How do I talk to your app? Because I don't want to have to click through menus.
"Artificial intelligence" encompasses a vast range of technologies - like traditional logic and rules-based systems - that enable computers and robots to mimic human solve problems in ways that at least superficially resemble thinking.
Within that realm is a smaller category called "machine learning", which is the name for a whole toolbox of arcane but important [statistical] mathematical techniques that enable computers to improve at performing tasks with experience.
Finally, within machine learning is the smaller subcategory called "deep learning", [composed of algorithms that permit software to train itself to perform tasks by exposing multilayered neural networks to vast amounts of data.]
"Most of AI was inspired by logic back then. But logic is something people do very late in life. Kids of 2 and 3 aren't doing logic. So it seemed to me that neural nets were a much better paradigm for how intelligent would work than logic was." - Geoffrey Hinton
"...because it was very difficult at that time actually to publish a paper if you mentioned the word 'neurons' or 'neural nets'. So he wrote this paper in an obfuscated manner so it would pass the reviewers... - Yann LeCun
In 1997 IBM's Deep Blue beats world champion Garry Kasparov in chess using traditional AI techniques.
In 2011 IBM's Watson beats two champions at Jeopardy using traditional AI techniques.
In 2014 Google bought DeepMind, whose deep reinforcement learning project, AlphaGo, defeated the world's go champion, Less Sedol, achieving an artificial intelligent landmark.
Unlike IBM's Deep Blue, which defeated chess champion Garry Kasparov in 1997, AlpahGo was not programmed with decision trees, or equations on how to evaluate board positions, or with if-then rules.
Does that mean it's time to brace for "the singularity"? [...] Not just yet. Neural nets are good at recognizing patterns - sometimes as good as or better than we are at it. But they can't reason.