Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 38 references that are in the map. First posted on arXiv 27 Apr 2021.
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References · 9
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
- 2015SSD: Single Shot MultiBox Detectorcited by 3,130
- 2017Multimodal Machine Learning: A Survey and Taxonomycited by 1,013
- 2019Generalizing from a Few Examples: A Survey on Few-Shot Learningcited by 463
- 2017Learning Explanatory Rules from Noisy Datacited by 211
- 2019CUDA-Self-Organizing feature map based visual sentiment analysis of bank customer complaints for Analytical CRMcited by 2
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