Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence

TL;DR

This paper reviews key developments in AI, proposes a classification into human, machine, and biological intelligence, and discusses standards for AI research directions and methodologies.

Contribution

It introduces a new framework categorizing AI into human, machine, and biological intelligence, guiding future research and application development.

Findings

Review of 'Once learning' and 'One-shot learning' successes

Proposal of AI classification into three main categories

Discussion of classification standards and research directions

Abstract

This article reviews the "Once learning" mechanism that was proposed 23 years ago and the subsequent successes of "One-shot learning" in image classification and "You Only Look Once - YOLO" in objective detection. Analyzing the current development of Artificial Intelligence (AI), the proposal is that AI should be clearly divided into the following categories: Artificial Human Intelligence (AHI), Artificial Machine Intelligence (AMI), and Artificial Biological Intelligence (ABI), which will also be the main directions of theory and application development for AI. As a watershed for the branches of AI, some classification standards and methods are discussed: 1) Human-oriented, machine-oriented, and biological-oriented AI R&D; 2) Information input processed by Dimensionality-up or Dimensionality-reduction; 3) The use of one/few or large samples for knowledge learning.