Emerging Trends and Future Directions in Artificial Intelligence for Next‐Generation Computing
Year: 2024
Type: other
Abstract: The progress of artificial intelligence depends on new hardware infrastructures being developed to overcome the constraints of conventional computers, such as the von Neumann bottleneck. Two-dimensional materials can emulate artificial neural networks (ANNs) with high performance to develop devices with artificial synaptic behavior using low power consumption through memristor configurations. New materials and devices must be proposed to exploit artificial intelligence, and the options that have shown greater efficiency and versatility are linked to the application of two-dimensional materials. In this way, nanotechnology can be exploited in basic research to implement applications based on new emerging materials. Among the two-dimensional materials that have been used for the implementation of memristors are graphene, phosphorene (BP), hexagonal boron nitride ( h -BN), transition metal dichalcogenides (TMDs), MXenes, etc.The purpose of this chapter is to review the advances achieved so far and predict the technological and scientific trends that will enable the practical implementation of neuromorphic computing to exploit artificial intelligence in high-speed computing and large amounts of data.
Author: Rafael Vargas‐Bernal
Institution: Universidad de Guanajuato
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Funder: Universidad de Guanajuato
OpenAlex ID: W4404251924