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Nov 23
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A new kind of hybrid artificial intelligence is offering theoretical physicists a powerful collaborator in the quest to find deeper laws of physics newscientist.com/article/mg2563…

In 1980, Stephen Hawking considered the possibility of a theory of everything that would unite general relativity and quantum mechanics – our two leading descriptions of reality – into one neat, all-encompassing equation We would need some help, he reckoned, from computers
Equations neatly capture the relations between physical stuff

Jim Stephenson/View Pictures/Universal Images Group via Getty Images
Artificial intelligence has achieved much since then and yet theoretical physicists have been slow to adopt it This is largely because the deep-learning algorithms behind AIs spit out answers that amount to a “what” rather than a “why” newscientist.com/definition/art…
But now, physicists have found a way to make deep-learning algorithms speak their language They can leverage AI’s ability to scour vast data sets in search of hidden patterns and extract meaningful results – namely, equations newscientist.com/article/mg2543…
“We’re moving into the discovery phase,” says Steve Brunton (@Steven Brunton) at @University of Washington
By combining deep learning and a technique called symbolic regression - which essentially runs through various possible mathematical operations and combinations of physical variables - AIs are able rediscover known laws of physics from raw data, such as Newton's laws of gravity
Applied to the glut of new astrophysical data, an algorithm called PySR is beginning to discover new equations that describe diverse and interrelated features of the cosmos
Raymond Biesinger
Pablo Lemos (@Pablo Lemos) at @Université de Montréal, who was involved in AI’s rediscovery of Newton’s law of gravity, suspects that symbolic regression could soon weigh into debates about the nature of dark matter and dark energy newscientist.com/article/mg2443…
NASA's Goddard Space Flight Center Conceptual Image Lab/Science Photo Library
Meanwhile, physicists are trying to figure out which bits of the human theorist’s playbook should be enshrined in their machine counterparts and which should be left out to make sure they don’t get stuck in the same ways we have newscientist.com/article/mg2533…
Now that physicists and artificial intelligence have found a common language, we might see a new kind of collaboration “It feels to me like the beginning of a sea change,” says Jesse Thaler at @Massachusetts Institute of Technology (MIT) To learn more, read @Thomas Lewton’s feature: newscientist.com/article/mg2563…
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