Authors: George Rajna
Scientists led by Daigo Shoji from the Earth-Life Science Institute (Tokyo Institute of Technology) have shown that a type of artificial intelligence called a convolutional neural network can be trained to categorize volcanic ash particle shapes.  Intel's Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration.  Artificial intelligence is astonishing in its potential. It will be more transformative than the PC and the Internet. Already it is poised to solve some of our biggest challenges.  In the search for extraterrestrial intelligence (SETI), we've often looked for signs of intelligence, technology and communication that are similar to our own.  Call it an a-MAZE-ing development: A U.K.-based team of researchers has developed an artificial intelligence program that can learn to take shortcuts through a labyrinth to reach its goal. In the process, the program developed structures akin to those in the human brain. 
Comments: 44 Pages.
[v1] 2018-06-27 08:19:23
Unique-IP document downloads: 14 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.