Intelligence at any price? A criterion for defining AI

IF 2.9 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE AI & Society Pub Date : 2023-06-01 DOI:10.1007/s00146-023-01695-0

Mihai Nadin

引用次数: 0

Abstract

According to how AI has defined itself from its beginning, thinking in non-living matter, i.e., without life, is possible. The premise of symbolic AI is that operating on representations of reality machines can understand it. When this assumption did not work as expected, the mathematical model of the neuron became the engine of artificial “brains.” Connectionism followed. Currently, in the context of Machine Learning success, attempts are made at integrating the symbolic and connectionist paths. There is hope that Artificial General Intelligence (AGI) performance can be achieved. As encouraging as neuro-symbolic AI seems to be, it remains unclear whether AGI is actually a moving target as long as AI itself remains ambiguously defined. This paper makes the argument that the intelligence of machines, expressed in their performance, reflects how adequate the means used for achieving it are. Therefore, energy use and the amount of data necessary qualify as a good metric for comparing natural and artificial performance.

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不惜任何代价的智力?定义AI的标准

根据人工智能从一开始就对自己的定义，在非生命物质中思考，也就是说，没有生命，是可能的。符号人工智能的前提是，在现实表象上操作的机器可以理解它。当这个假设没有像预期的那样起作用时，神经元的数学模型就成了人工“大脑”的引擎。联结主义。目前，在机器学习成功的背景下，人们试图整合符号和连接路径。人工通用智能(AGI)的性能有望实现。尽管神经符号人工智能似乎令人鼓舞，但只要人工智能本身的定义仍然含糊不清，就不清楚AGI是否真的是一个移动的目标。本文提出的论点是，机器的智能，表现在它们的性能上，反映了实现它所使用的手段有多充分。因此，能源使用和必要的数据量有资格作为比较自然和人工性能的良好指标。

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来源期刊

AI & Society COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

8.00

自引率

20.00%

发文量

257

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