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Related papers: Has our brain grown too big to think effectively?

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The central nervous system and particularly the brain was designed to control the life cycle of a living being. With increasing size and sophistication, in mammals, the brain became capable of exercising significant control over life. In…

History and Philosophy of Physics · Physics 2016-05-09 M N Vahia

The "Machiavellian intelligence" hypothesis (or the "social brain" hypothesis) posits that large brains and distinctive cognitive abilities of humans have evolved via intense social competition in which social competitors developed…

Populations and Evolution · Quantitative Biology 2009-11-13 Sergey Gavrilets , Aaron Vose

Background: Human populations during the last 10,000 years have undergone rapid decreases in average brain size as measured by endocranial volume or as estimated from linear measurements of the cranium. A null hypothesis to explain the…

Populations and Evolution · Quantitative Biology 2011-03-01 John Hawks

The last few million years on planet Earth have witnessed two remarkable phases of hominid development, starting with a phase of biological evolution characterised by rather rapid increase of the size of the brain. This has been followed by…

Populations and Evolution · Quantitative Biology 2015-05-20 Brandon Carter

It is proposed that the ability of humans to flourish in diverse environments and evolve complex cultures reflects the following two underlying cognitive transitions. The transition from the coarse-grained associative memory of Homo habilis…

Neurons and Cognition · Quantitative Biology 2013-08-26 Liane Gabora , Diederik Aerts

This paper summarizes efforts to computationally model two transitions in the evolution of human creativity: its origins about two million years ago, and the 'big bang' of creativity about 50,000 years ago. Using a computational model of…

Neural and Evolutionary Computing · Computer Science 2019-07-11 Liane Gabora , Steve DiPaola

Growth in brain volume is one of the most spectacular changes in the hominid lineage. The anthropological community agrees on that point. No consensus, however, has been reached on selection pressures contributing to that growth. In that…

Populations and Evolution · Quantitative Biology 2013-12-20 Konrad R. Fialkowski

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes…

Neurons and Cognition · Quantitative Biology 2011-12-23 Marcus Kaiser , Sreedevi Varier

How did the human species evolve the capacity not just to communicate complex ideas to one another but to hold such conversations from across the globe, using remote devices constructed from substances that do not exist in the natural…

Neurons and Cognition · Quantitative Biology 2019-07-09 Liane Gabora , Anne Russon

At the core of our uniquely human cognitive abilities is the capacity to see things from different perspectives, or to place them in a new context. We propose that this was made possible by two cognitive transitions. First, the large brain…

Neurons and Cognition · Quantitative Biology 2019-07-11 Liane Gabora , Kirsty Kitto

Many species engage in acts that could be called creative. However, human creativity is unique in that it has transformed our planet. Given that the anatomy of the human brain is not so different from that of the great apes, what enables us…

Neurons and Cognition · Quantitative Biology 2019-07-11 Liane Gabora , Scott Barry Kaufman

Drawing upon a body of research on the evolution of creativity, this paper proposes a theory of how, when, and why the forward-thinking story-telling abilities of humans evolved, culminating in the visionary abilities of science fiction…

Neurons and Cognition · Quantitative Biology 2019-03-15 Liane Gabora

For long it has been known that specific patterns of folding are necessary for an optimally functioning brain. For instance, lissencephaly and polymicrogyria can lead to severe mental retardation, short life expectancy, epileptic seizures,…

Biological Physics · Physics 2020-04-03 Lucas da Costa Campos , Raphael Hornung , Gerhard Gompper , Jens Elgeti , Svenja Caspers

A few million words suffice for children to acquire language. Yet, the brain mechanisms underlying this unique ability remain poorly understood. To address this issue, we investigate neural activity recorded from over 7,400 electrodes…

We provide a birds eye view of the rapid developments in AI and Deep Learning that has led to the path-breaking emergence of AI in Large Language Models. The aim of this study is to place all these developments in a pragmatic broader…

Artificial Intelligence · Computer Science 2024-05-20 Arifa Khan , P. Saravanan , S. K Venkatesan

The cerebrum of mammals spans a vast range of sizes and yet has a very regular structure. The amount of folding of the cortical surface and the proportion of white matter gradually increase with size, but the underlying mechanisms remain…

Neurons and Cognition · Quantitative Biology 2022-06-14 Marc H. E. de Lussanet

Human populations have a complex history of introgression and of changing population size. Human genetic variation has been affected by both these processes, so that inference of past population size depends upon the pattern of gene flow…

Populations and Evolution · Quantitative Biology 2017-03-29 John Hawks

Research on emergent patterns in Large Language Models (LLMs) has gained significant traction in both psychology and artificial intelligence, motivating the need for a comprehensive review that offers a synthesis of this complex landscape.…

Computation and Language · Computer Science 2024-12-23 Zhisheng Tang , Mayank Kejriwal

Creativity is perhaps what most differentiates humans from other species. It involves the capacity to shift between divergent and convergent modes of thought in response to task demands. Divergent thought has been characterized as the kind…

Neurons and Cognition · Quantitative Biology 2019-12-03 Liane Gabora

Large language models (LLMs) solve complex problems yet fail on simpler variants, suggesting they achieve correct outputs through mechanisms fundamentally different from human reasoning. To understand this gap, we synthesize cognitive…

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