相关论文: Human-Level Intelligence or Animal-Like Abilities?

What if a clock could do more than tell time - what if it could look around? This project explores the conceptualization, design, and construction of a timepiece with visual perception capabilities, featuring three types of human-time…

Vision-language models (VLMs) hold promise for enhancing visualization tools, but effective human-AI collaboration hinges on a shared perceptual understanding of visual content. Prior studies assessed VLM visualization literacy through…

As multimodal machine intelligence systems started achieving average animal-level and average human-level fluency in many measurable tasks in processing images, language, and sound, they began to exhibit a new class of cognitive…

As progress in AI continues to advance, it is important to know how advanced systems will make choices and in what ways they may fail. Machines can already outsmart humans in some domains, and understanding how to safely build ones which…

Large language models (LLMs) are capable of writing grammatical text that follows instructions, answers questions, and solves problems. As they have advanced, it has become difficult to distinguish their output from human-written text.…

We test the abilities of specialised deep neural networks like PersonalityMap as well as general LLMs like GPT-4o and Claude 3 Opus in understanding human personality. Specifically, we compare their ability to predict correlations between…

Non-human primates (NHPs), especially rhesus macaques, have played a significant role in our current understanding of the neural computations underlying human vision. Apart from the established homologies in the visual brain areas between…

A simple electrical network model, having logical gate capacities, is proposed here for computations in plant cells. It is compared and contrasted with the animal brain network structure and functions.

A deep understanding of the dynamics of the human nervous system requires the simultaneous study of multiple spatiotemporal scales from the level of neurotransmitters up to the level of human cultures. This is likely impossible for…

Artificial Neural Networks (ANNs) were devised as a tool for Artificial Intelligence design implementations. However, it was soon became obvious that they are unable to fulfill their duties. The fully autonomous way of ANNs working,…

Evaluating reasoning ability in Large Language Models (LLMs) is important for advancing artificial intelligence, as it transcends mere linguistic task performance. It involves understanding whether these models truly understand information,…

There is no denying the tremendous leap in the performance of machine learning methods in the past half-decade. Some might even say that specific sub-fields in pattern recognition, such as machine-vision, are as good as solved, reaching…

In this paper we explore hallucinations and related capability limitations in LLMs and LLM-based agents from the perspective of computational complexity. We show that beyond a certain complexity, LLMs are incapable of carrying out…

The Turing Test is no longer adequate for distinguishing human and machine intelligence. With advanced artificial intelligence systems already passing the original Turing Test and contributing to serious ethical and environmental concerns,…

A comparison between human and Generative AI decision-making attributes in complex health services is a knowledge gap in the literature, at present. Humans may possess unique attributes beneficial to decision-making in complex health…

Deep convolutional neural networks follow roughly the architecture of biological visual systems and have shown a performance comparable to human observers in object recognition tasks. In this study, I tested three pretrained deep neural…

A definition of Artificial Intelligence was proposed in [1] but this definition was not absolutely formal at least because the word "Human" was used. In this paper we will formalize the definition from [1]. The biggest problem in this…

Intelligence is a difficult concept to define, despite many attempts at doing so. Rather than trying to settle on a single definition, this article introduces a broad perspective on what intelligence is, by laying out a cascade of…

We identify a fundamental incompatibility between the goals of accuracy, trust, and human-level reasoning in artificial intelligence (AI) systems, for strict mathematical definitions of these notions. We define accuracy of a system as the…

Physical emergence - crystals, rocks, sandpiles, turbulent eddies, planets, stars - is fundamentally different from biological emergence - amoeba, cells, mice, humans - even though the latter is based in the former. This paper points out…