The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe

The Extraordinary Link Between Deep Neural Networks and the Nature of the Universe

seem like a bot summary

In the last few years, deep learning techniques have transformed the world of artificial intelligence. One by one, the abilities and techniques that humans once imagined were uniquely our own have begun to fall to the onslaught of ever more powerful machines. Deep neural networks are now better than humans at tasks such as face recognition and object recognition. They’ve mastered the ancient game of Go and thrashed the best human players.

But there is a problem. There is no mathematical reason why networks arranged in layers should be so good at these challenges. Mathematicians are flummoxed. Despite the huge success of deep neural networks, nobody is quite sure how they achieve their success.

That's changed, thanks to the work of Henry Lin at Harvard University and Max Tegmark at MIT in 2016. These guys say the reason why mathematicians have been so embarrassed is that the answer depends on the nature of the universe. In other words, the answer lies in the regime of physics rather than mathematics.

"These guys say the reason why mathematicians have been so embarrassed is that the answer depends on the nature of the universe. In other words, the answer lies in the regime of physics rather than mathematics."

I don't find this distinction convincing. Most of our ideas about the physics of the universe are expressed in the language of mathematics. Physics and mathematics are inextricably linked.

Funny isn't it?  The physicists speak of "explanations".  All of them, literally, are mathematical descriptions of physical reality.  Often the term "understanding" is used in favor of explanation.  What do we really "understand"?  It seems we see correlations between mathematical equations and human observations of the world around us.  A far cry from "understanding" to my view.