Bridging the Gap between Artificial Intelligence and Artificial General Intelligence: A Ten Commandment Framework for Human-Like Intelligence

TL;DR

This paper proposes a ten-commandment framework inspired by human intelligence to guide the development of more general, explainable, and higher-order artificial intelligence systems through a neuromorphic computational approach.

Contribution

It introduces a novel ten-commandment framework for human-like intelligence and suggests architectural modifications for creating more general and explainable AI systems.

Findings

Framework outlines essential ingredients for higher-order cognition

Proposes neuromorphic architectural modifications

Aims to develop more general and explainable AI

Abstract

The field of artificial intelligence has seen explosive growth and exponential success. The last phase of development showcased deep learnings ability to solve a variety of difficult problems across a multitude of domains. Many of these networks met and exceeded human benchmarks by becoming experts in the domains in which they are trained. Though the successes of artificial intelligence have begun to overshadow its failures, there is still much that separates current artificial intelligence tools from becoming the exceptional general learners that humans are. In this paper, we identify the ten commandments upon which human intelligence is systematically and hierarchically built. We believe these commandments work collectively to serve as the essential ingredients that lead to the emergence of higher-order cognition and intelligence. This paper discusses a computational framework that could house these ten commandments and suggests new architectural modifications that could lead to the development of smarter, more explainable, and generalizable artificial systems inspired by a neuromorphic approach.