Neural network -based symbolic integration outperforms Mathematica
Juha Järvi <[email protected]> Wed, 18 Dec 2019 12:16:04 +0200
| Newsgroups | gmane.games.devel.go |
|---|---|
| Message-ID | <CABugXTt45wFp3C0TQiyvQUqReTjOvcsUqrD6=egm3myfLPt+pA@mail.gmail.com> |
--===============7136813493384561663== Content-Type: multipart/alternative; boundary="0000000000009953910599f7bdb3" --0000000000009953910599f7bdb3 Content-Type: text/plain; charset="UTF-8" There's a new paper from Facebook AI research: https://arxiv.org/abs/1912.01412 8 GPUs and a few hours of training and the neural network can already solve symbolic integration tasks humans and Mathematica, Maple and Matlab cannot. Source: the author's tweet at https://twitter.com/GuillaumeLample/status/1202178956063064064 Interesting if the same phenomenon appeared in mathematics as in Go: professionals studying results from an AI -based algorithm trying to understand new techniques it has discovered. This seems like an interesting field similar to Go: huge set of possible inputs, lots of supposed creativity required to obtain correct result in complicated cases, hundreds of years of human research to reach the status quo, and a win condition (one of often many possible correct outputs in this case) that is easily checked. --0000000000009953910599f7bdb3 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">There's a new paper from Facebook AI research:<div><a = href=3D"https://arxiv.org/abs/1912.01412">https://arxiv.org/abs/1912.01412<= /a><br></div><div><br></div><div>8 GPUs and a few hours of training and the= neural network can already solve symbolic integration tasks humans and Mat= hematica, Maple and Matlab cannot. Source: the author's tweet at</div><= div><a href=3D"https://twitter.com/GuillaumeLample/status/12021789560630640= 64">https://twitter.com/GuillaumeLample/status/1202178956063064064</a><br><= /div><div><br></div><div>Interesting if the same phenomenon appeared in mat= hematics as in Go: professionals studying results from an AI -based algorit= hm trying to understand new techniques it has discovered.</div><div><br></d= iv><div>This seems like an interesting field similar to Go: huge set of pos= sible inputs, lots of supposed creativity required to obtain correct result= in complicated cases, hundreds of years of human research to reach the sta= tus quo, and a win condition (one of often many possible correct outputs in= this case) that is easily checked.</div><div><br></div></div> --0000000000009953910599f7bdb3-- --===============7136813493384561663== Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Content-Disposition: inline _______________________________________________ Computer-go mailing list [email protected] http://computer-go.org/mailman/listinfo/computer-go --===============7136813493384561663==--