Computational Intelligence for Autonomous Finance

14Emerging Trends and Future Directions in Artificial Intelligence for Next-Generation Computing

Rafael Vargas-Bernal

Departamento de Ingeniería Electrónica, DICIS, Universidad de Guanajuato, Salamanca, Guanajuato, Mexico

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.

Keywords: Artificial intelligence, neuromorphic computing, ...