Is Intelligence Artificial?
- URL: http://arxiv.org/abs/1403.1076v9
- Date: Wed, 17 Jul 2024 08:52:08 GMT
- Title: Is Intelligence Artificial?
- Authors: Kieran Greer,
- Abstract summary: This paper attempts to give a unifying definition that can be applied to the natural world in general and then Artificial Intelligence.
A metric that is grounded in Kolmogorov's Complexity Theory is suggested, which leads to a measurement about entropy.
A version of an accepted AI test is then put forward as the 'acid test' and might be what a free-thinking program would try to achieve.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Our understanding of intelligence is directed primarily at the human level. This paper attempts to give a more unifying definition that can be applied to the natural world in general and then Artificial Intelligence. The definition would be used more to qualify than quantify it and might help when making judgements on the matter. While correct behaviour is the preferred definition, a metric that is grounded in Kolmogorov's Complexity Theory is suggested, which leads to a measurement about entropy. A version of an accepted AI test is then put forward as the 'acid test' and might be what a free-thinking program would try to achieve. Recent work by the author has been more from a direction of mechanical processes, or ones that might operate automatically. This paper agrees that intelligence is a pro-active event, but also notes a second aspect to it that is in the background and mechanical. The paper suggests looking at intelligence and the conscious as being slightly different, where the conscious is this more mechanical aspect. In fact, a surprising conclusion can be a passive but intelligent brain being invoked by active and less intelligent senses.
Related papers
- Imagining and building wise machines: The centrality of AI metacognition [78.76893632793497]
We argue that shortcomings stem from one overarching failure: AI systems lack wisdom.
While AI research has focused on task-level strategies, metacognition is underdeveloped in AI systems.
We propose that integrating metacognitive capabilities into AI systems is crucial for enhancing their robustness, explainability, cooperation, and safety.
arXiv Detail & Related papers (2024-11-04T18:10:10Z) - On the consistent reasoning paradox of intelligence and optimal trust in AI: The power of 'I don't know' [79.69412622010249]
Consistent reasoning, which lies at the core of human intelligence, is the ability to handle tasks that are equivalent.
CRP asserts that consistent reasoning implies fallibility -- in particular, human-like intelligence in AI necessarily comes with human-like fallibility.
arXiv Detail & Related papers (2024-08-05T10:06:53Z) - Machine learning and information theory concepts towards an AI
Mathematician [77.63761356203105]
The current state-of-the-art in artificial intelligence is impressive, especially in terms of mastery of language, but not so much in terms of mathematical reasoning.
This essay builds on the idea that current deep learning mostly succeeds at system 1 abilities.
It takes an information-theoretical posture to ask questions about what constitutes an interesting mathematical statement.
arXiv Detail & Related papers (2024-03-07T15:12:06Z) - On a Functional Definition of Intelligence [0.0]
Without an agreed-upon definition of intelligence, asking "is this system intelligent?"" is an untestable question.
Most work on precisely capturing what we mean by "intelligence" has come from the fields of philosophy, psychology, and cognitive science.
We present an argument for a purely functional, black-box definition of intelligence, distinct from how that intelligence is actually achieved.
arXiv Detail & Related papers (2023-12-15T05:46:49Z) - AI for Mathematics: A Cognitive Science Perspective [86.02346372284292]
Mathematics is one of the most powerful conceptual systems developed and used by the human species.
Rapid progress in AI, particularly propelled by advances in large language models (LLMs), has sparked renewed, widespread interest in building such systems.
arXiv Detail & Related papers (2023-10-19T02:00:31Z) - The Nature of Intelligence [0.0]
The essence of intelligence commonly represented by both humans and AI is unknown.
We show that the nature of intelligence is a series of mathematically functional processes that minimize system entropy.
This essay should be a starting point for a deeper understanding of the universe and us as human beings.
arXiv Detail & Related papers (2023-07-20T23:11:59Z) - Suffering Toasters -- A New Self-Awareness Test for AI [0.0]
We argue that all current intelligence tests are insufficient to point to the existence or lack of intelligence.
We propose a new approach to test for artificial self-awareness and outline a possible implementation.
arXiv Detail & Related papers (2023-06-29T18:58:01Z) - An argument for the impossibility of machine intelligence [0.0]
We define what it is to be an agent (device) that could be the bearer of AI.
We show that the mainstream definitions of intelligence' are too weak even to capture what is involved when we ascribe intelligence to an insect.
We identify the properties that an AI agent would need to possess in order to be the bearer of intelligence by this definition.
arXiv Detail & Related papers (2021-10-20T08:54:48Z) - Inductive Biases for Deep Learning of Higher-Level Cognition [108.89281493851358]
A fascinating hypothesis is that human and animal intelligence could be explained by a few principles.
This work considers a larger list, focusing on those which concern mostly higher-level and sequential conscious processing.
The objective of clarifying these particular principles is that they could potentially help us build AI systems benefiting from humans' abilities.
arXiv Detail & Related papers (2020-11-30T18:29:25Z) - Machine Common Sense [77.34726150561087]
Machine common sense remains a broad, potentially unbounded problem in artificial intelligence (AI)
This article deals with the aspects of modeling commonsense reasoning focusing on such domain as interpersonal interactions.
arXiv Detail & Related papers (2020-06-15T13:59:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.