Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 1 through 15 of 99 found.

Planatural Genesis: A Phenomenal, PhiloSophia, Propaedutic, TwinKinder, Participatory Endeavor

Ahmed, Nafeez. “Planetary phase shift” as a new systems framework to navigate the evolutionary transformation of human civilization. Foresight. November 2024, . In this Emerald Insight journal, a British investigative journalist, author and academic contributes a rare composite, global overview by which to perceive a crucial transitional event. T

The paper advances futures study and practice by an example of a unified theoretical framework across a wide range of different ecological, social, political and economic systems. It proposes a new “collective forward intelligence” that can make sense of their trends as symptoms of a wider planetary sphere and to also construct plausible scenarios to underpin national and international decision-making. This study focusses on a transdisciplinary integration of C. S. Holling’s (search) adaptive environmental cycle with phase-transition phenomena across biology, physics and chemistry, applied on societal and civilizational scales. (Abstract)

Aschwanden, Martin. Power Laws in Astrophysics: Self-Organized Criticality Systems. Cambridge: Cambridge University Press, 2025.. Cambridge: Cambridge University Press, 2025. The author has studied observations and theoretical models of self-organized criticality systems for over 40 years as a researcher based at Lockheed Martin Solar and Astrophysics Laboratory. This latest edition follows his 2011 work Self-Organized Criticality in Astrophysics: Statistics of Nonlinear Processes in the Universe, along with many collegial projects and writings (search) before and after. For recent work see Universal Constants and Energy Integral in Self-Organized Criticality Systems at arXiv:2412.03481 (reviewed) and Testing the Universality of Self-Organized Criticality in Galactic, Extra-Galactic, and Black-Hole Systems at arXiv:2412.03499.

Research applications of complex systems and nonlinear physics are rapidly expanding across scientific disciplines. A common theme among them is the concept of “self-organized criticality systems”, which this volume presents for astrophysical phenomena such as solar flares, planetary systems, galactic and black-hole systems. The work explores why do power laws, self-organized criticality, an a universality actually exist? A highlight is a paradigm shift from microscopic concepts, such as cellular automaton algorithms, to macroscopic concepts formulated in terms of physical scaling laws.

Di Ieva, Antonio, ed.. The Fractal Geometry of the Brain. Switzerland: Springer, 2024. This second, expanded edition since 2016 can exemplify the rapid, wide-ranging, research-based confirmation and adoption of this invariant topological frame everywhere. We include some typical entries in the quote section, along with other current papers. Our web survey now covers four decades from Benoit Mandelbrot in the 1980s as nature’s own mathematical, artistic self-similarity has come to to grace and brace every occasion from cerebral facilities to atomic, social and celestial phases. For our 2024/2025 great turning to Turing moment, this 1,000 page volume contributes still another source by which to affirm and record our actual Earthuman discovery of a familiar spacetime universality.

Along with search Di Ieva for the 2016 volume, see also Self-similarity in pandemic spread and fractal containment policies by Siegenfeld, Alexander, et al (Yaneer Bar-Yam) at arXiv:2412.09021, Complexity synchronization analysis of neurophysiological data by Ioannis Schizas, et ai (Bruce West) at arXiv:2411.14602 and The interdisciplinary journey to fractal bionics by Richard Taylor in Physics Today (77/12), 2024.

By way of 48 authoritative chapters over several sections, The Fractal Geometry of the Brain reviews the many intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and issues. The volume brings an understanding of fractals to clinicians and research without needing a mathematical background, and serves as a valuable tool for teaching the translational applications of computational fractal-based models. (Book)

The introduction of fractal geometry to the neurosciences has been a major paradigm shift over the last decade which has overcome limitations of Euclidean and reductionist approaches are used to analyze neurons or the entire brain. Fractal analysis provides a quantitative study of the morphology of brain cells (neurons and microglia) and its components (dendritic trees, synapses), as well as the brain structure (cortex, functional modules, neuronal networks). The self-similar logic which generates and shapes the hierarchical systems of the brain is widely discussed in the following chapters. (Fractals in Neuroanatomy and Basic Neurosciences, A. Di Ieva)

The evolution of the brain in mammals is due to changes in size, architecture, and internal organization. Consequently, the geometry of the brain, and the size and shape of the cerebral cortex, has changed notably during evolution. In this chapter, some of the design principles and operational modes that underlie the fractal geometry and information processing capacity of the cerebral cortex in primates, including humans, will be explored. It is shown that the cortex coordinates fold with connectivity in a way that produces smaller and faster brains. (The Fractal Geometry of the Human Brain: An Evolutionary Perspective, Michel Hofman)

The fractal dimension of cognition refers to the idea that the cognitive processes of the human brain exhibit fractal properties. This means that certain patterns of cognitive activity, such as visual perception, memory, language, or problem-solving, can be described using the mathematical concept of fractal dimension. (Fractals in Neuropsychology and Cognitive Neuroscience, Antonio Cerasa)

In this chapter, we will investigate the significance of fractals for the human senses. We propose that fractals with mid-range complexity play a unique role because our visual system has adapted to these prevalent natural patterns. This fluency optimizes the observer’s capabilities (such as pattern recognition) and generates an aesthetic experience. We will also compare these responses to research focused on fractal sounds and surface textures. (Fractal Fluency: Processing of Fractal Stimuli Across Sight, Sound, and Touch, Richard Taylor, et al)

Antonio Di Ieva, MD, PhD, is Professor of Neurosurgery at the Macquarie Medical School, Macquarie University, Sydney, Australia.

Dodig-Crnkovic, Gordana. Reimagining Life: Emergent Complexity from Non-Living to Living.. preprints.org/manuscript/202411.1827/v1.. The Chalmers University of Technology, Sweden natural philosopher (search) provides another luminous essay which proceeds to survey and integrate the nonlinear systems revolution from the 1980s into the 2010s and today. As the Abstract cites, a cogent theoretical gathering of contributors to nonequilibrium thermodynamics, self-organized criticality, symbiogenesis, complex adaptive systems (John Holland), teleodynamics (T. Deacon), autopoiesis and onto ecological aspects (Simon Levin) is reviewed and tabulated into a uniquely thorough chronicle, In this year of convergent syntheses, it is high time to put everything back together and wonder at the natural universe to human genesis that is just now being revealed.

The paper highlights its central themes of self-organization, emergence, and the interplay between physical, informational, and biological processes. Ilya Prigogine’s concept of dissipative structures and irreversibility provided a foundation for understanding complexity in physical systems, which later expanded into biology through Stuart Kauffman’s models of creativity and evolution. Lynn Margulis's endosymbiosis theory further illumines the cooperative dynamics of life’s vitality, while Sara Walker's work integrates thermodynamics and information theory to bridge chemistry and biology via multiscale interactions and adaptive dynamics. As a synthesis of these views, this article situates life as an emergent phenomenon across many scales which defines a unified framework to understand complex cognizance in the natural world.

Conclusion. Toward a Unified Paradigm of Complexity From Prigogine’s thermodynamics to Walker’s information theory, these thinkers collectively advance our understanding of life and complexity. Their contributions converge on the rejection of reductionism, emphasizing the active properties of matter—such as self-assembly and self-organization—along with emergence, creativity, and the dynamic interplay between physical and informational processes that shape life in the natural world. (9)

Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Actual Factual Twintelligent Knowledge

Agrawal, Aakash and Stanislas Dehaene.. Cracking the neural code for word recognition in convolutional neural networks. PLoS Computational Biology. September, 2024. Université Paris-Saclay system neurolinguists (search SD) deeply describe how complex, code-like processes are able to discern textual alphabetic scripts and sentence forms. In regard it would seem that our ascendant human cerebral faculties are indeed made and meant to become literate, recognize and comprehend.

• Learning to read places a burden on the visual system as it becomes able to separate similar letters and encode their relative positions, thus viewing words over a large range of positions, sizes and fonts. Here, we address this by recycling deep neural network models for image recognition and retrain to recognize written words. We can then analyze how reading-specialized units emerge and operate. The proposed literacy scheme provides a neural code for written words in the visual word form area, and leads can predict reading behavior so to inform the neurophysiology of reading. (Excerpt)

Overall, we delineate the stages of orthographic processing that lead to invariant visual word recognition. Beyond reading, the proposed hierarchical scheme for moving from retinotopic to ordinal-position codes extends to the recognition of the configuration of parts within an object. The same mechanism would also encode the position of parts, not only to left/right, but also to top/bottom, as required for mathematical or musical notations. Finally, while we focused entirely on the endpoint of learning, the present work could easily be extended to study the developmental emergence of letter position codes in both models and children [6].

Krakauer, David. Exbodiment: The Mind Made Matter.. arXiv:2412.10957.. A unique entry by the SFI polyscholar and past president is worth notice as an innovative exercise in natural philosophy, broadly conceived, that courses from classical music to beehives, spider webs, chess boards and winds up with Stanislav Lem’s book Solaris whereby global matter and mentation also seem trying to figure out whatever may be going on.

Exbodiment describes mind outsourced to engineered matter and how matter reeducates mind. The constraints of exbodied matter encode elements of thought, channel decision-making, and constitute an important part of an extended computational phenotype. Here I provide an introduction and brief cultural history of exbodiment in music, natural history, cognition, and astrobiology. The "Helix of Exbodiment" is introduced to illustrate continuous feedback between mind and matter.

The (bee) hive and combs are part of the system of computation required for effective foraging. And like an abacus and a slide rule, employ persistent features of physical geometry to allow for very precise behavior. A foraging bee is part body, part collective, and part physical hive. The functional unit of navigation – analog to Chopin’s Bauza preludes and Jarrett’s Bosendorfer Koln concert — is a behavior embedded in a life-constructed physics. (3)

Ngomane, Mungi. Everyday Ubuntu: Living Better Together, the African Way.. New York: Harper, 2020. In this beautiful definitive guide, Mungi Ngomane, granddaughter of Nobel Peace Prize laureate Desmond Tutu, offers a heart-felt introduction to ubuntu, the indigenous African philosophy that celebrates a true complementary human community, aka” it takes an (eco)village.” It is illustrated with full-color photos and filled with lessons on how to live harmoniously with all people and an organic nature. See also Ubuntutu: Tributes to Archbishop Desmond and Leah Tutu by Quilt Artists from South Africa and the United States by Marsha MacDowell, et al, eds. (Michigan State University Museum, 2017).

Ubuntu is a Xhosa word for South African wisdom about a universal human bond: I am only because you are. By embracing the philosophy of ubuntu and living it out in daily life it’s possible to overcome division and be stronger together in a world where the wise build bridges, not walls. These 14 lessons can help us to live better, together. In stories that recognize our common humanity, our connectedness and interdependence, Everyday Ubuntu make sense of the world and our place in it. Exploring ideas of kindness and forgiveness, tolerance and the power of listening, it shows how we can benefit from embracing others.

Mungi Ngomane is the granddaughter of Archbishop Desmond Tutu and patron of the Tutu Foundation UK. She has worked in Middle East conflict resolution and for the advancement of women and girls for advocacy organizations and initiatives. She hopes one day all girls will have FUNdamental human rights. She has a Master’s in International Studies and Diplomacy from the School of Oriental and African Studies at the University of London.

Allen, Alice and Kimberly DuPrie. Ten reasons to register your software with the Astrophysics Source Code Library. arXiv:2412.19941. We cite this entry by AA, Astrophysics Source Code Library, Houghton, MI and KD, Space Telescope Science Institute, Baltimore to convey the extent that global scientific projects presently involve and rely on deep computational programs. Altogether into 2025 a composite worldwise sapience could be viewed as learning on her/his prodigious own.

This presentation covers the benefits of registering astronomy research software with the Astrophysics Source Code Library, a free online registry for software used in astronomy research. Making your software available shows confidence in your research and makes it more transparent, reproducible, and falsifiable. Adding your code to the 3600 entries already in ASCL allows others to find your version easily, also in ADS, Web of Science, and Google Scholar. (Excerpt)

The Astrophysics Source Code Library is a free online registry and repository for source codes of interest to astronomers and astrophysicists. The ASCL is indexed by the SAO/NASA Astrophysics Data System (ADS) and Web of Science and is citable by using the unique ascl ID assigned to each code. Here next is a sample entry:

[ascl:2412.023] cogsworth: Self-consistent population synthesis and galactic dynamics simulations, Tom Wagg, et al. cogsworth merges rapid population synthesis and galactic dynamics so the code can evolve a population of stars while self- integrating their orbits.

Lovell, Christopher, et al. Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours.. arXiv:2411.13960. We place this entry by twelve astrophysicists at the University of Portsmouth, UK, Northwestern University, Columbia University, University of Connecticut, University of Edinburgh, CCNY, University College London, University of Sussex, Flatiron Institute, NYC and Princeton University including Rachel Somerville and Francisco Villaescusa-Navarro in this section about an emergent sapiensphere learning on her/his own because it represents a large scientific project at many locales. In addition, its title cites an ordained endeavor and mission that our Earthumanity (mostly unbeknownst) has embarked upon. It might even seem that a participatory ecosmos has ordained we sentient beings with a necessary task of self-description and observance.

We perform the first cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours. We study the ultraviolet--near infrared stellar emission from galaxies in thousands of cosmological hydrodynamic simulations from the CAMELS suite and Astrid galaxy formation models. Both colour distributions and luminosity functions provide complementary information since the photometry encodes the star formation--metal enrichment history of each galaxy. (Excerpt sample)

Bengio, Yoshua, et al. International Scientific Report on the Safety of Advanced AI.. arXiv:2412.05282.. This 132 page document is the report from the May 2024 AI Seoul Summit conference. An authoritative array of computer experts and business contributors, just about everybody, and a huge audience gave the event an international significance. Topical presentations emphasized both AG Intelligences while trying to get in front of many ethical ramifications. As a reference, we cite the original 2015 “Deep Learning” article by Yann LeCun, Y. Bengio and Gregory Hinton (Nature 521/436) only nine years ago for a sense of how fast and furious this global (knowsphere) facility is moving. We had better get ahold of the reins and steering wheel in time.

This is the interim publication of The first International Scientific Report on the Safety of Advanced AI. The report synthesises the scientific understanding of general-purpose AI -- AI that can perform a wide variety of tasks -- with a focus on understanding and managing its risks. A diverse group of 75 AI experts contributed to this report, including an international Expert Advisory Panel nominated by 30 countries, the EU, and the UN.

People around the world will only be able to enjoy general-purpose AI’s many potential benefits safely if its risks are appropriately managed. This report focuses on identifying these risks and evaluating technical methods for assessing and mitigating them. It does not aim to comprehensively assess all possible societal impacts of general-purpose AI, including its many potential benefits.

Eacersall, Douglas, et al. The ETHICAL Framework for Responsible Generative AI Research Use. arXiv:2501.09021.. Fifteen cultural scholars mainly in Australia along with Canada, Malayasia and the Philippines post a thorough cast of behavioral standards and regulations so to insure at this early stage that trustworthy results are achieved.

The rapid adoption of generative artificial intelligence (GenAI) presents both many opportunities and ethical issues that should be carefully navigated. This paper develops the ETHICAL guide as a practical guide for responsible GenAI use by way of seven key principles: Examine policies and guidelines, Think about social impacts, Harness understanding of the technology, Indicate use, Critically engage with outputs, Access secure versions, and Look at user agreements. (Excerpt)

The ETHICAL Framework presented in this article stands as a foundational resource for researchers navigating the ethical challenges associated with GenAI. While some guidelines exist, this framework progresses beyond awareness to practical action. The ETHICAL Framework explicitly equips researchers with actionable principles, providing clear guidance on ethical GenAI use in research, thereby supporting both integrity and impact. (17)

Gifford, Alessandro, et al. The Algonauts Project 2025 Challenge.. arXiv:2501.00504. Freie Universität Berlin, Goethe Universität Frankfurt, Université de Montréal, Montréal and MIT neuroscientists including Radoslaw Cichy describe an array of innovate AI adventures as a way to better understand how brains perform and may interface with computational media. An example would Automating the Search for Artificial Life with Foundation Models at pub.sakana.ai/asal, second quote.

There is growing symbiosis between artificial and biological intelligence sciences: neural principles inspire new intelligent machines, which are in turn used to advance our theoretical understanding of the brain. Here we introduce the 2025 edition: How the Human Brain Makes Sense of Multimodal Movies. In collaboration with the Courtois Project on Neuronal Modelling, our aim is to bring forth a new generation of brain encoding models that generalize well by training them on large datasets of fMRI responses. (Excerpt)

Artificial Life (ALife) has not yet integrated FMs which presents an opportunity to move beyond manual design and trial-and-error to discover of lifelike simulations. The proposed approach, called Automated Search for Artificial Life (ASAL), (1) finds simulations that produce target phenomena, (2) that generate temporally open-ended novelty, and (3) illuminates an entire space of interestingly diverse versions. A major result is finding novel Lenia and Boids lifeforms, as well as open-ended cellular automata. (Sanaka MIT)

A foundation model is a deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. Generative AI applications like Large Language Models are examples. (Wikipedia)

Gonçalves, Bernado. Passed the Turing Test: Living in Turing Futures. Intelligent Computing. Vol 3/Art 0102, 2024. We note this entry by a Center for Artificial Intelligence, University of São Paulo computer scientist for its content and his perception that such Turing devices would likely be akin to youngsters as they assimilate their environs.

The world has seen the emergence of machines based on pretrained models, transformers for their ability to produce various types of content, text, images, audio, and synthetic data. Their intelligence grows as they learn from experience, and to ordinary people, they can appear human-like in conversation. This means that they can pass the Turing test and that we are now living in one of the futures where machines can pass for what they are not. However, the learning machines that Turing imagined would pass his imitation tests were they based on the low-energy human cortex. They would be raised like human children and naturally learn the ability to deceive an observer. (Excerpt)

Bernardo Gonçalves For the past six years, my research has focused on the future of AI as envisioned by Alan Turing, the foundations and ethics of AI, and the future of machines in society & nature. I have 12+ years of R & D experience in AI and data-centric systems in academia and industry. I am a Researcher at the Center for AI (C4AI) of the University of São Paulo and a Visiting Fellow in History and Philosophy of Science at Cambridge University.

Kumar, Akarsh, et al. Automating the Search for Artificial Life with Foundation Models. .. arXiv:2412.17799. MIT, Sakana AI, OpenA, and Swiss AI Lab IDSIA computational imagineers describe their frontier excursions as novel approaches to juice the A Life endeavor to see how it can respectfully and beneficially open frontier pathways. See also Automating the Search for Artificial Life with Foundation Models at pub.sakana.ai/asal for a companion paper.

With the recent Nobel Prize awarded for radical advances in protein discovery, foundation models (FMs) for exploring large combinatorial spaces promise to revolutionize many scientific fields. This paper presents a successful realization using vision-language FMs called Automated Search for Artificial Life (ASAL), finds generalities across a diverse range of ALife substrates including Boids, Particle Life, Game of Life, Lenia, and Neural Cellular Automata. This new paradigm promises to accelerate ALife research beyond what is possible through human ingenuity alone. (Excerpt)

A foundation model is a deep machine learning method trained on vast datasets so it can be applied across a wide range of use cases. Early examples are language models (LMs) like OpenAI's GPT. Foundation models are also being developed for fields like astronomy, radiology, genomics, mathematics, and chemistry.

Pandey, Lalit, et al. Parallel development of object recognition in newborn chicks and deep neural networks. PLoS Computational Biology. December, 2024. Indiana University informatics researchers including Justin and Samantha Wood describe a clear correspondence between these title phases of cognitive performance by way of a novel usage of digital twins and AI learning methods. As a result, a continuity can be traced between these computational and personal occasions. In regard, here is one more instance where parallels can be drawn between AI procedures and young organisms (chicks and children). See also Parallel development of social behavior in biological and artificial fish in Nature Communications (15/1061, 2024) by this group. A further notice would then be how nature consistently uses the same pattern and process over and over everywhere.

How do newborns learn to see? We propose that visual systems are space-time fitters, meaning that visual development can be understood as a blind fitting process (akin to evolution) which gradually adapts to the spatiotemporal environments. To test whether space-time fitting is a viable theory, we performed parallel controlled-rearing experiments on newborn chicks and deep neural networks (DNNs), including CNNs and transformers. When DNNs received the same training data as chicks, the models developed common object recognition skills as chicks. We argue that space-time fitters can serve as scientific models of newborn visual systems. (Excerpt)

We present evidence for parallel development of object recognition in newborn chicks and deep neural networks. Like chicks, the models learned invariant object features from visual experiences in impoverished environments, permitting recognition of familiar objects across large, novel, and complex changes in the object’s appearance. This digital twin approach extends the reverse-engineering framework pioneered in computational neuroscience to the study of newborn vision, supporting the broader goal of building unified models of the learning machinery in brains. (26)

One of the unsolved mysteries in science concerns the origins of intelligence. By linking psychology to artificial intelligence, we aim to reverse engineer the origins of intelligence and build machines that learn like newborn animals. I am interested in a wide range of questions about the origins and nature of intelligence. I have studied the psychological abilities of diverse human adults, toddlers, infants, chimpanzees, wild monkeys, and newborn chicks. (J. Wood website)

1 | 2 | 3 | 4 | 5 | 6 | 7  Next