嵌入式世界与人工智能

IF 2.1 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Mostafa Haghir Chehreghani
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引用次数: 0

摘要

从早期开始,人工智能界的一个关键和有争议的问题就是人工通用智能(AGI)是否可以实现。AGI 是指机器和计算机程序能够实现人类水平的智能,并能完成人类所能完成的所有任务。虽然文献中存在一些声称实现了 AGI 的系统,但其他一些研究人员则认为不可能实现 AGI。首先,我们讨论了为了实现 AGI,在构建智能机器和程序的同时,还应该构建一个智能世界,这个世界一方面是我们这个世界的精确近似,另一方面,智能机器的大部分推理已经嵌入了这个世界。然后,我们讨论了 AGI 并不是一种产品或算法,而是一个持续的过程,随着时间的推移会变得越来越成熟(就像人类文明和智慧一样)。然后,我们认为预训练嵌入在构建这个智能世界以及实现 AGI 的过程中发挥着关键作用。我们讨论了预训练嵌入如何促进机器实现人类智能的几个特征,如体现、常识性知识、无意识知识和持续学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The embeddings world and Artificial General Intelligence

From early days, a key and controversial question inside the artificial intelligence community was whether Artificial General Intelligence (AGI) is achievable. AGI is the ability of machines and computer programs to achieve human-level intelligence and do all tasks that a human being can. While there exist a number of systems in the literature claiming they realize AGI, several other researchers argue that it is impossible to achieve it.

In this paper, we take a different view to the problem. First, we discuss that in order to realize AGI, along with building intelligent machines and programs, an intelligent world should also be constructed which is on the one hand, an accurate approximation of our world and on the other hand, a significant part of reasoning of intelligent machines is already embedded in this world. Then we discuss that AGI is not a product or algorithm, rather it is a continuous process which will become more and more mature over time (like human civilization and wisdom). Then, we argue that pre-trained embeddings play a key role in building this intelligent world and as a result, realizing AGI. We discuss how pre-trained embeddings facilitate achieving several characteristics of human-level intelligence, such as embodiment, common sense knowledge, unconscious knowledge and continuality of learning, by machines.

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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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