Home > News > Combining Nanowires and Memristors Could Lead to Brain-like Computing
April 4th, 2013
Combining Nanowires and Memristors Could Lead to Brain-like Computing
Abstract:
For decades now, researchers have been trying to get computers to behave like artificial brains instead of merely binary data crunchers. One of the obstacles in creating this capability has been that computers are based on silicon CMOS chips rather than the dendrites and synapses found in the human brain. One of the drawbacks with silicon chips is that they lack what is known as "plasticity" in which the brain's neurons adapt in order to learn and remember.
To overcome such limitations, nanotechnology has been offering alternatives to silicon chip architecture that will more closely resemble the human brain. DARPA's SyNAPSE project is one example.
Now researchers at the Centre for Research on Adaptive Nanostructures and Nanodevices (CRANN) at Trinity College in Dublin are pursuing a new nanomaterial-based approach to neural networks that combines work in nanowires and memristors. The aim of the project, for which the researchers have just received a €2.5 million research grant from the European Research Council (ERC), is to develop a new computing paradigm that mimics the neural networks of the human brain. A video describing the CRANN research can be seen below.
Source:
spectrum.ieee.org
Bookmark:
| Related News Press |
News and information
Decoding hydrogen‑bond network of electrolyte for cryogenic durable aqueous zinc‑ion batteries January 30th, 2026
COF scaffold membrane with gate‑lane nanostructure for efficient Li+/Mg2+ separation January 30th, 2026
Videos/Movies
ICFO researchers overcome long-standing bottleneck in single photon detection with twisted 2D materials August 8th, 2025
New X-ray imaging technique to study the transient phases of quantum materials December 29th, 2022
Solvent study solves solar cell durability puzzle: Rice-led project could make perovskite cells ready for prime time September 23rd, 2022
Brain-Computer Interfaces
Taking salt out of the water equation October 7th, 2022
Blog sites
First measurement of electron energy distributions, could enable sustainable energy technologies June 5th, 2020
Novel Electrode Structure Provides New Promise for Lithium-Sulfur Batteries December 3rd, 2016
Peter Diamandis Thinks Nanotech Will Interface With Human Minds September 1st, 2016
Graphene-Enabled Paper Makes for Flexible Display August 1st, 2016
Chip Technology
Metasurfaces smooth light to boost magnetic sensing precision January 30th, 2026
Beyond silicon: Electronics at the scale of a single molecule January 30th, 2026
Lab to industry: InSe wafer-scale breakthrough for future electronics August 8th, 2025
Discoveries
From sensors to smart systems: the rise of AI-driven photonic noses January 30th, 2026
Decoding hydrogen‑bond network of electrolyte for cryogenic durable aqueous zinc‑ion batteries January 30th, 2026
COF scaffold membrane with gate‑lane nanostructure for efficient Li+/Mg2+ separation January 30th, 2026
Announcements
Decoding hydrogen‑bond network of electrolyte for cryogenic durable aqueous zinc‑ion batteries January 30th, 2026
COF scaffold membrane with gate‑lane nanostructure for efficient Li+/Mg2+ separation January 30th, 2026
Artificial Intelligence
From sensors to smart systems: the rise of AI-driven photonic noses January 30th, 2026
New quantum encoding methods slash circuit complexity in machine learning November 8th, 2024
Rice research could make weird AI images a thing of the past: New diffusion model approach solves the aspect ratio problem September 13th, 2024
 |
||
 |
||
| The latest news from around the world, FREE | ||
 |
||
|
|
||
| Premium Products | ||
 |
||
|
Only the news you want to read!
Learn More |
||
 |
||
|
Full-service, expert consulting
Learn More |
||
|
|
||