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

Authors: Li Weigang, Liriam Enamoto, Denise Leyi Li, Geraldo Pereira Rocha Filho

This article reviews the Once Learning mechanism and divides Artificial Intelligence into three categories: Artificial Human Intelligence (AHI), Artificial Machine Intelligence (AMI), and Artificial Biological Intelligence (ABI). The paper is with 16 pages and 3 tables
License: CC BY 4.0

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.

Submitted to arXiv on 27 Apr. 2021

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Beta

Look for similar papers (in beta version)

We compare the title and abstract with papers indexed in our database. For arXiv papers, we search within the same category; for DOI and other sources, we search across sources and subjects. You can rerun the search as our database grows.