Open AccessEmergence of In‐Materio Intelligence from an Incidental Structure of a Single‐Walled Carbon Nanotube–Porphyrin Polyoxometalate Random Network
Author(s) -
Banerjee Deep,
Kotooka Takumi,
Azhari Saman,
Usami Yuki,
Ogawa Takuji,
Gimzewski James K.,
Tamukoh Hakaru,
Tanaka Hirofumi
Publication year - 2022
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202270014
Subject(s) - polyoxometalate , porphyrin , carbon nanotube , artificial intelligence , computer science , robot , feature (linguistics) , object (grammar) , nanotechnology , materials science , chemistry , catalysis , biochemistry , linguistics , philosophy , photochemistry
In‐Materio Reservoir Computing In article number 2100145 , Hirofumi Tanaka and co‐workers have developed an in‐materio reservoir computing (RC) system with a random network of single‐walled carbon nanotube/porphyrin‐polyoxometalate and demonstrated robot‐based object classification. Time‐series tactile inputs picked up by a haptic sensor at the robot‐arm are converted to multiple high feature outputs using the system and finally trained to separate each object. The in‐materio RC system is intended to be implemented as an artificial intelligence for robotic applications near future.