Self‐Programming Synaptic Resistor Circuit for Intelligent Systems. (18th May 2021)
- Record Type:
- Journal Article
- Title:
- Self‐Programming Synaptic Resistor Circuit for Intelligent Systems. (18th May 2021)
- Main Title:
- Self‐Programming Synaptic Resistor Circuit for Intelligent Systems
- Authors:
- Shaffer, Christopher M.
Deo, Atharva
Tudor, Andrew
Shenoy, Rahul
Danesh, Cameron D.
Nathan, Dhruva
Gamble, Lawren L.
Inman, Daniel J.
Chen, Yong - Abstract:
- Abstract : Unlike artificial intelligent systems based on computers which have to be programmed for specific tasks, the human brain "self‐programs" in real time to create new tactics and adapt to arbitrary environments. Computers embedded in artificial intelligent systems execute arbitrary signal‐processing algorithms to outperform humans at specific tasks, but without the real‐time self‐programming functionality, they are preprogrammed by humans, fail in unpredictable environments beyond their preprogrammed domains, and lack general intelligence in arbitrary environments. Herein, a synaptic resistor circuit that self‐programs in arbitrary and unpredictable environments in real time is demonstrated. By integrating the synaptic signal processing, memory, and correlative learning functions in each synaptic resistor, the synaptic resistor circuit processes signals and self‐programs the circuit concurrently in real time with an energy efficiency about six orders higher than those of computers. In comparison with humans and a preprogrammed computer, the self‐programming synaptic resistor circuit dynamically modifies its algorithm to control a morphing wing in an unpredictable aerodynamic environment to improve its performance function with superior self‐programming speeds and accuracy. The synaptic resistor circuits potentially circumvent the fundamental limitations of computers, leading to a new intelligent platform with real‐time self‐programming functionality for artificialAbstract : Unlike artificial intelligent systems based on computers which have to be programmed for specific tasks, the human brain "self‐programs" in real time to create new tactics and adapt to arbitrary environments. Computers embedded in artificial intelligent systems execute arbitrary signal‐processing algorithms to outperform humans at specific tasks, but without the real‐time self‐programming functionality, they are preprogrammed by humans, fail in unpredictable environments beyond their preprogrammed domains, and lack general intelligence in arbitrary environments. Herein, a synaptic resistor circuit that self‐programs in arbitrary and unpredictable environments in real time is demonstrated. By integrating the synaptic signal processing, memory, and correlative learning functions in each synaptic resistor, the synaptic resistor circuit processes signals and self‐programs the circuit concurrently in real time with an energy efficiency about six orders higher than those of computers. In comparison with humans and a preprogrammed computer, the self‐programming synaptic resistor circuit dynamically modifies its algorithm to control a morphing wing in an unpredictable aerodynamic environment to improve its performance function with superior self‐programming speeds and accuracy. The synaptic resistor circuits potentially circumvent the fundamental limitations of computers, leading to a new intelligent platform with real‐time self‐programming functionality for artificial general intelligence. Abstract : A synaptic resistor (synstor) circuit emulates the real‐time self‐programming functionality of the human brain by processing signals and self‐programming synstor conductance matrix w concurrently. The synaptic resistor circuit potentially circumvents the fundamental limitations of computers, leading to a new intelligent platform to spontaneously improve its performance function F in unpredictable and arbitrary environments for artificial general intelligence. … (more)
- Is Part Of:
- Advanced intelligent systems. Volume 3:Number 8(2021)
- Journal:
- Advanced intelligent systems
- Issue:
- Volume 3:Number 8(2021)
- Issue Display:
- Volume 3, Issue 8 (2021)
- Year:
- 2021
- Volume:
- 3
- Issue:
- 8
- Issue Sort Value:
- 2021-0003-0008-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2021-05-18
- Subjects:
- artificial general intelligence -- neuromorphic circuits -- self-programming -- synaptic resistors
Artificial intelligence -- Periodicals
Robotics -- Periodicals
Control theory -- Periodicals
006.3 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
https://onlinelibrary.wiley.com/journal/26404567 ↗ - DOI:
- 10.1002/aisy.202100016 ↗
- Languages:
- English
- ISSNs:
- 2640-4567
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 18555.xml