25 papers · ranked by Valyu relevance
Jürgen Jost
We investigate the basic principles of structural knowledge. Structural knowledge underlies cognition, and it organizes, selects and assigns meaning to information. It is the result of evolutionary, cultural and developmental processes. Because of its own constraints, it needs to discover and exploit regularities and…
Igor Rudan
This editorial explores the concept of the ‘value of information’ in the 21st century through five distinct domains: science, medicine, policy, media, and markets. It uses examples to show that not all information is of equal value. Valuable information shifts probabilities assigned to our hypotheses in the most…
Stephanie Nelli, Lukas Braun, Tsvetomira Dumbalska, Andrew Saxe + 1 more
Human understanding of the world can change rapidly when new information comes to light, such as when a plot twist occurs in a work of fiction. This flexible “knowledge assembly” requires few-shot reorganisation of neural codes for relations among objects and events. However, existing computational theories are largely…
Yunus A. Çengel, Kevin H. Knuth, Gordana Dodig-Crnkovic
The term information is used in different meanings in different fields of study and daily life, causing misunderstanding and confusion. There is a need to clarify what information is and how it relates to knowledge. It is argued that information is meaning represented by physical symbols such as sights, sounds, and…
Yoram Moses, Marcia K. Shamo
—In a supervisory control system the human agent's knowledge of past, current, and future system behavior is critical for system performance. Being able to reason about that knowledge in a precise and structured manner is central to effective system design. In this paper we introduce the application of a…
Alexander Krauss
Few things have impacted our lives as much as science and technology, but how we developed science and civilisation is one of the most challenging questions that has not yet been well explained. Attempting to identify the central driver, leading scientists have highlighted the role of culture, cooperation and…
Aaron Chatterji, Daniel Rock, Eduard Talamas
Nonaka emphasized that innovation is the result of a continuous back-and-forth between tacit and explicit knowledge. Artificial intelligence introduces a fundamentally new object into this process -- tacit machine knowledge -- but Nonaka's ideas are more relevant than ever. The central role of the knowledge-creating…
George Leu, Hussein A. Abbass
This paper offers a multi-disciplinary review of knowledge acquisition methods in human activity systems. The review captures the degree of involvement of various types of agencies in the knowledge acquisition process, and proposes a classification with three categories of methods: the human agent, the human-inspired…
Romain Ligneul, Martial Mermillod, Tiffany Morisseau
Epistemic curiosity (EC) is a cornerstone of human cognition that contributes to the actualization of our cognitive potential by stimulating a myriad of information-seeking behaviours. Yet, its fundamental relationship with uncertainty remains poorly understood, which limits our ability to predict within- and…
Jonathan Najenson, Nir Fresco
Knowledge-how is the kind of knowledge implicated in skill employment and acquisition. Intellectualists claim that knowledge-how is a special type of propositional knowledge. Anti-intellectualists claim that knowledge-how is not propositional. We argue that both views face two open challenges. The first challenge…
Constanza Fierro, Ruchira Dhar, Filippos Stamatiou, Nicolas Garneau + 1 more
'Anders Søgaard'] Knowledge claims are abundant in the literature on large language models (LLMs); but can we say that GPT-4 truly "knows" the Earth is round? To address this question, we review standard definitions of knowledge in epistemology and we formalize interpretations applicable to LLMs. In doing so, we…
Fernando Baquero
In the field of observational and experimental natural sciences (as is the case for microbiology), recent decades have been overinfluenced by overwhelming technological advances, and the space of abstraction has been frequently disdained. However, the predictable future of biological sciences should necessarily recover…
Leonardo Fernandino, Jia-Qing Tong, Lisa L. Conant, Colin J. Humphries + 1 more
The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with…
F. Luyckx, H. Nili, B. Spitzer, C. Summerfield
Humans can learn abstract concepts that describe invariances over relational patterns in data. One such concept, known as magnitude, allows stimuli to be compactly represented by a single dimension (i.e. on a mental line), for example according to their cardinality, size or value. Here, we measured representations of…
Stefanie Meliss, Carien van Reekum, Kou Murayama
Curiosity – the intrinsic desire to know – is a concept central to the human mind and knowledge acquisition. Experimental studies on information-seeking have found that curiosity facilitates memory encoding and exhibits similar reward,ng properties as extrinsic rewards/incentives by eliciting a dopaminergic response.…
Antoni Gomila, Vincent C. Müller
The declared goal of this paper is to fill this gap: "… cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress." – the quotation being from the project description…
Stefaan Blancke, Maarten Boudry
Modern democratic societies tend to appeal to the authority of science when dealing with important challenges and solving their problems. Nevertheless, distrust in science remains widespread among the public, and, as a result, scientific voices are often ignored or discarded in favour of other perspectives. Though…
Włodzisław Duch
The complexity of cultures in the modern world is now beyond human comprehension. Cognitive sciences cast doubts on the traditional explanations based on mental models. The core subjects in humanities may lose their importance. Humanities have to adapt to the digital age. New, interdisciplinary branches of humanities…
Authors not listed
We have developed Aitomia – a platform powered by AI to assist in performing AI-driven atomistic and quantum chemical (QC) simulations. This evolving intelligent assistant platform is equipped with chatbots and AI agents to help experts and guide non-experts in setting up and running atomistic simulations, monitoring…
Philippe Desjardins-Proulx, Timothée Poisot, Dominique Gravel
Artificial Intelligence presents an important paradigm shift for science. Science is traditionally founded on theories and models, most often formalized with mathematical formulas handcrafted by theoretical scientists and refined through experiments. Machine learning, an important branch of modern Artificial…
Zhichu Ren, Zhen Zhang, Yunsheng Tian, Ju Li
Autonomous laboratories were previously controlled mainly by scripting languages such as Python, limiting their usage among experimentalists. The recent release of OpenAI's ChatGPT API's function calling feature has enabled seamless integration and execution of Python subroutines in experimental workflows using voice…
Yasmine Nahal, Janosch Menke, Julien Martinelli, Markus Heinonen + 5 more
Machine learning (ML) systems have enabled the modelling of quantitative structure-property relationships (QSPR) and structure-activity relationships (QSAR) using existing experimental data to predict target properties for new molecules. These property predictors hold significant potential in accelerating drug…
Iiris Sundin, Alexey Voronov, Haoping Xiao, Kostas Papadopoulos + 5 more
A de novo molecular design workflow can be used together with technologies such as reinforcement learning to navigate the chemical space. A bottleneck in the workflow that remains to be solved is how to integrate human feedback in the exploration of the chemical space to optimize molecules. A human drug designer still…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
Authors not listed
Nuclear Magnetic Resonance (NMR) structure determination is an important problem in education, industry, and research. Solving NMR spectra requires expert knowledge, critical thinking, and careful evaluation of multiple features of spectral data. This study explores the capabilities of large language models (LLMs) for…