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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Recent Additions

Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 1 through 15 of 107 found.

> Geonativity

, . Van Schependom, Jeroen, et al. Neurophysiological avenues to better conceptualizing adaptive cognition. Communications Biology. 7/626, 2024.. Communications Biology. 7/626, 2024. Vrije Universiteit Brussel, Oxford University, CNR Istituto dei Sistemi Complessi, Italy and Technical University Dresden neuroscientists achieve another deeply quantified notice and expression of a reciprocal balance between coincident opposites of more or less coherence, conservation or creativity. Once again a semblance of a critically organized “sweet spot” appears as a natural optimum preference. We write on June 28 and wonder how can these robust, universal scientific findings ever make it to an academe stuck in mechanist denials of anything going on at all. We respectfully offer herein a Planatural PhiloSophia family mind and a PediaPedia Earthica.

We delve into the human brain’s deep capacity for adaptability and cognitive functioning, which are often seen as an executive domain. In regard, the neural bases that enable the navigation between transient thoughts without detracting from overarching goals form our article. We discuss the concept of “metacontrol,” which proposes a dynamic balancing of core processes depending on situational demands. This approach leads to the role of oscillatory processes in electrophysiological activity at different phases of desynchronization and synchronization in supporting adaptive behavior. These cognitive and neurophysiological avenues can thereby contribute to a more nuanced comprehension and its neural basis in both health and disease. (Excerpt)

Our central focus lies in exploring cognitive processing along a continuum characterized by its two polar phases: “persistence” and “flexibility.” We propose to use signal-processing methods to characterize this continuum connecting neurophysiology, physics, and cognitive science. (2)

> Geonativity

Castro, Daniel. et al. In and Out of Criticality? State-Dependent Scaling in the Rat Visual Cortex. PRX Life. 2/023008, 2024. In this new Physical Review journal, eight Universidade Federal de Pernambuco, Recife, Brazil and University of Minho, Braga, Portugal system physicians add a latest appreciation of how our cerebral processes indeed do seem to bounce around a best performance balance.

A presumed proximity to a critical point is believed to endow the brain with scale-invariant statistics to confer advantages for information processing, storage, and transmission. To assess scaling and cortical states, we apply a renormalization group method to data recordings from the anesthetized rat's visual cortex. Under anesthesia, cortical states shift across synchronization levels defined by population spiking rate variability. We find that scaling signatures only appear as spiking frequency surpasses a threshold. Our results suggest that a wide range of cortical states corresponds to small deviations around a critical point, with the system fluctuating in and out of criticality, spending roughly three-quarters of the experiment duration within a scaling regime. (Abstract excerpt)

Our Planatural Edition: A 21st Century PhiloSophia, EarthTwinity, Ecosmic WumanVersion

The Genesis Vision > Historic Precedents

Rosen, Robert. Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life. New York: Columbia University Pres, 2005. The author (1934 - 1998) was a professor of theoretical biophysics at Dalhousie University in Halifax, Nova Scotia but his lifetime project was to move beyond, decades ago, an olden machine fixation by articulating how all manner of organisms are living systems, along with the whole natural world. In regard, Predrag Slijepčević new book Biocivilisations: A New Look at the Science of Life (Chelsea Green, 2023) takes up Rosen’s mission. And I once met spoke with RR in 1987 at a Boston University Philosophy of Science conference.)

The Genesis Vision > News

Bruckner, David and Gasper Tkacik. Bruckner, David and Gasper Tkacik. Information content and optimization of self-organized developmental systems.. PNAS. 121/23, 2024. Institute of Science and Technology (ITSA), Austria physicists introduce a novel framework to study self-organized, reaction-diffusion patterning as a stochastic dynamical system. As the quotes say, their proof of principle is the way cells form, migrate and combine in. embryonic development. See also then Waves, patterns, bifurcations: the vertebrate segmentation clock by Paul Francois and Victoria Mochulska in Physics Reports (Volume 1080, 2024) and Precise and scalable self-organization in mammalian pseudo-embryos by Melody Merle and Leah Friedman in Nature Structural & Molecular Biology. (31/896, 2024) for similar, concurrent reports of the same theoretical basis.

Altogether this year, along with many other entries, our 21st century, 2020s prodigious revolution has reached a robust wide and deep observance of a phenomenal universe to pediaverse catalytic spontaneity which now seems to require its own aware, selective realization. An awesome consequence then accrues for our Earthuman observance. We valiant, survivor peoples may well be the actual SELVES whom altogether are meant to respectfully take up, vitalize, engender and continue to arrange a universal procreativity.

Development relies on the ability of cells to self-organize into patterns of different cell types that underlie the formation of tissues and organs. But how to generically quantify the patterning performance of different biological self-organizing systems has remained unclear. Here, we develop an information-theoretic framework to analyze a wide range of models of self-organization. Our approach can be used to define the information content of observed patterns, assess the importance of regulatory motifs, and predict optimal operating regimes for self-organizing systems. In regard, this framework achieves a unifying mathematical language to describe the actual presence of biological self-organization across diverse systems. (Significance)

Self-organizing patterning processes generate, transmit, transform, and distribute information in space and time. Much as physics equips us with a formalism to describe how the flows of matter take shape, information theory provides a formal language to quantify statistical structures. This approach has previously been applied to formalize the notion of “positional information” in developmental systems, where inputs are the maternally provided morphogen gradients. However, for self-organizing patterns a more general approach is needed to quantify their information content. Here, we address this challenge by proposing an information-theoretic measure of self-organization performance in embryonic development. (2)

New mathematical framework sheds light on how cells communicate to form an embryo
Biological processes depend on puzzle pieces coming together and interacting. Interestingly, the mammalian embryo develops similarly. In nature, self-organization is all around us: We can observe it in fish schools, bird flocks, or insect collectives, and even in microscopic processes regulated by cells. "Information theory is a universal language to quantify structure and regularity in statistical ensembles, which are a collection of replicates of the same process. Embryonic development can be seen as such a process that reproducibly generates functional organisms that are very similar but not identical," says Gašper Tkačik, professor at ISTA and expert in this field. (ITSA News)

The Genesis Vision > News

Frank, Adam, et al. The Blind Spot: Why Science Cannot Ignore Human Experience.. Cambridge: MIT Press, 2024. . As this decade goes on, senior scholars AF, University of Rochester, MG, Dartmouth College and ET, University of British Columbia convened for some time to come to the realization that a main lacunae of 21st century thought was the exclusion of any human place and relevance in a cosmic to cultural scenario, which is then relegated to accidental. While scientific descriptions achieved by our sapient acumen run from muons to a multiverse, it is rarely imagined that our present learned occasion has any other phenomenal or participatory account.

In The Blind Spot, astrophysicist Adam Frank, cosmologist Marcelo Gleiser, and philosopher Evan Thompson call for a revolutionary scientific worldview which includes humanity as a vital part of objective truth. For centuries people have looked to science to tell us who we are, where we come from, and where we’re going, but without our own inclusion. This Blind Spot impedes our learning about the universe, quantum physics, life, AI, mind, consciousness, and Earth as a precious planet. As a result, we can view ourselves as an intended source of nature’s self-understanding, going forward in the new millennium.

The Genesis Vision > News

Kogut, Alan, et al. Kogut, Alan, et al. The Primordial Inflation Explorer (PIXIE): Mission Design and Science Goals. arXiv:2405.20403. We note this posting by seventeen astroscientists from across the USA, onto the UK, France and beyond led by NASA Goddard which detailed project plans as Earthropo sapiens proceeds apace with the task of astronomic self-quantification. See also The SKA Galactic Centre Survey: A White Paper at arXiv:2406.04022. Along with many similar endeavors, what a grand scenario is altogether revealed whence our unique knowsphere commences on an intrinsic course of (multi)universal self-quantification, representation, and select affirmation.

The Primordial Inflation Explorer (PIXIE) mission concept plans to measure the energy spectrum and linear polarization of the cosmic microwave background (CMB). PIXIE opens a broad discovery space for the origin, contents, and evolution of the universe. Measurements of small distortions from a CMB blackbody spectrum provide a robust determination of the mean electron pressure and temperature in the universe while constraining processes including dissipation of primordial density perturbations, black holes, and the decay or annihilation of dark matter. We describe the PIXIE instrument sensitivity, foreground subtraction, and anticipated science return from both the baseline 2-year mission and a potential extended mission. (Excerpt)

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

A Learning Planet > The Spiral of Science

Sante, Andrea, et al. Applying machine learning to Galactic Archaeology. arXiv:2405.00102. Five Liverpool John Moores University astroscientists consider whether the ancient timeline origin of stars in the Milky Way can be presently quantified by virtue of these novel AI data dense facilities. And once again, one might reflect on the whole scenario of a creative ecosmos whose regnant life evolves to a collaborative sapience on an infinitesimal bioplanet that is able to achieve such nascent self-representations. We wonder what kind of universe reality seems to require its own observance, recognition and aware admission to bring itself into full existence. See also A Census of Sun's Ancestors and their Contributions to the Solar System Chemical Composition by F. Fiore, et al at 2406.08036 and Presolar Grains by Nan Liu at 2406.14694.

We survey machine learning (ML) models developed to separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These methods, which include examples from artificial neural networks, decision trees and dimensionality reduction techniques, are trained on a sample of disc-like, Milky Way-mass galaxies. We find that the input parameters consist of stellar positions, kinematics, chemical abundances and photometric properties. The general applicability bodes well for application to identify accreted substructures in the Milky Way. (Excerpt)

A Learning Planet > Mindkind Knowledge

Huh, Minyoung, et al.. Huh, Minyoung, et al. The Platonic Representation Hypothesis. . Neural networks, trained with different objectives on different data and modalities, are converging to a shared statistical model of reality in their representation spaces. We cite this May entry by MIT computer scientists including Phillip Isola as an example of how these many large language models could be altogether seen as coming to their own planetary universion discovery. See also Learning and Leveraging World Models in Visual Representation Learning by Quentin Garrido, et al at arXiv:2403.00504. As incendiary conflicts worsen, the novel presence of an intelligent sapiensphere, aka an actual global brain, learning on her/his own could bring a salutary alternative we so need.

We argue that representations in AI models by way of deep neural networks, are in a convergence stage. First, we survey many examples in the literature over time and across multiple domains. Next, we demonstrate common trends across data modalities: as vision and language models get larger, they measure distance between datapoints in similar forms. We propose that this convergence is heading toward a shared statistical model of the world, akin to Plato's concept of an ideal reality. We dub this occasion as a platonic representation and discuss possible selective pressures toward it. Finally, we consider knowledgeable implications of these trends, within limits. (Abstract)

Our central hypothesis is that the representation we are converging toward is a statistical model of an underlying reality that generates our observations. Consistent with the multitask scaling hypothesis, such an appreciation would naturally be useful toward many tasks. Additionally, this worldview might be relatively simple, assuming that scientists are correct in suggesting that the fundamental laws of nature are indeed simple functions (Gell-Mann, 1995), in line with the simplicity bias hypothesis. (7)

Phillip Isola is an assistant professor and a principal investigator in MIT’s Computer Science and Artificial Intelligence Laboratory. His work focuses on why we represent the world the way we do, and how we can replicate these abilities in digital forms. Before coming to MIT, he was a visiting research scientist at OpenAI. He earned a PhD in brain and cognitive sciences at MIT and spent two years as a postdoc at the University of California, Berkeley.

A Learning Planet > Mindkind Knowledge > deep

Strachan, James, et al. Testing theory of mind in large language models and humans. Nature Human Behaviour. May, 2024. Into 2024, twelve computational neuroscientists posted in Germany, Italy, the UK and USA can begin to notice basic affinities between our own cerebral cognition and perceptive capabilities in these nascent cyberspace faculties. See also The Platonic Representation Hypothesis by Minyoung Huh, et al. arXiv:2405.07987 and Predicting the next sentence (not word) in large language models by Shaoyun Yu, et al in Science Advancesfor May 2024. Altogether a viable sense of a global brain as it envelopes the biosphere becomes evident. As these many articles contend, for better or worse depending on how well we might understand and moderate.

At the core of what defines us as humans is the concept of theory of mind: the ability to be aware of other people’s mental states. The development of large language models (LLMs) such as ChatGPT has led to the possibility that they exhibit behaviour similar to our theory of mind tasks. Here we compare human and LLM performance from understanding false beliefs to interpreting indirect requests and recognizing irony. We found that GPT-4 models performed at human levels for indirect requests, false beliefs and misdirection, but struggled with faux pas. These findings show that LLMs are consistent with mentalistic inference in humans and highlight the need for testing to ensure valid comparisons between human and artificial intelligences. (Abstract)

As artificial intelligence (AI) continues to evolve, it also becomes increasingly important to heed calls for open science to these models. Direct access to the parameters, data and documentation used to construct models can allow for targeted probing and experimentation into the key parameters affecting social reasoning, informed by and building on comparisons with human data. As such, open models can not only serve to accelerate the development of future AI technologies but also serve as models of human cognition. (7)

A Learning Planet > Mindkind Knowledge > deep

Suleyman, Mustafa. The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma. New York: Crown, 2023. As the quotes say, a “life” guard is sounding the alarm that a tsunami is building as a computational, algorithmic, multitudinous prowess based on brains poses to take off on its own. Impressive technologies of (genetic) life and of (artificial) intelligence are described which presage a synthetic revolution frontier whence our human innovations and interventions have the potential to commence a new intentional phase of evolutionary cocreation. So the issue is whether the wave front can pass to our aware Earthropic ethical benefit, or sweep over us. We are approaching a critical threshold in the history of our species. Soon you will live surrounded by AIs which will organize your life, operate your business, and run government services. It will involve DNA printers, quantum computers, autonomous weapons, robot assistants and abundant energy. As co-founder of DeepMind, now part of Google, Mustafa Suleyman has been at the center of this revolution. The coming decade, he argues, will be defined by this wave of powerful, proliferating technologies. As our fragile governments often sleepwalk into disaster, we face unprecedented harms on one side, and the threat of overbearing surveillance on the other. Can we forge a narrow path between catastrophe and dystopia?

Mustafa Suleyman is the CEO of Microsoft AI. Previously he co-founded and was the CEO of Inflection AI, and he also co-founded DeepMind, one of the world's leading AI companies.

Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

Animate Cosmos > Organic

Coleman, Gavin and William DeRocco. Predicting the Galactic population of free-floating planets from realistic initial conditions. arXiv:2407.05992. We cite this entry by Queen Mary University of London and UC, Santa Cruz exophysicists for its content as it gathers and conveys an early quantified observance of an interstellar spacescape populated with diverse planetary entities. See also Resonant and Ultra-short-period Planet Systems are at Opposite Ends of the Exoplanet Age Distribution at arXiv:2407.04765 for another view.

But then in regard, we wonder if this milieu might be imagined as some manner of amniotic ocean suffused with potential ovular or seed-like objects. Indeed a prior article entitled An Amniotic Universe by Carl Sagan in the Atlantic Monthly (April 1979) does evoke a fluid cosmic fertility. Anyway, these musings are the sort of total reconception, decades later, that our revolutionary worldwise science invites.

We present the first prediction for the mass distribution function of Galactic free-floating planets (FFPs) that aims to include multiple formation pathways and stellar populations. We derive our results from simulations of planet birth, growth, migration, circumbinary systems and from wide binary systems. We find that interactions with circumbinary systems are the main progenitor for FFPs more massive than Earth, leading to a power-law that agrees well with the observations. In contrast, we find -planet scatterings likely produce planets at Mars mass and below, with a shallower power-law. The features we predict in the mass distribution of FFPs will be detectable by upcoming space-based microlensing surveys. (Excerpt)

Animate Cosmos > Organic

D'Eugenio, Francesco, et al. JADES: Carbon enrichment 350 Myr after the Big Bang in a gas-rich galaxy.. arXiv:2311.09908.. As the awesome Webb telescope continues to send a stream of fantastic images from the outmost reaches, UK, USA, Australia, France, Italy, Germany, Japan, Spain report an even deeper probe into the onset appearance of metallic elements and compounds which can then engender a prebiotic milieu. Into 2024, might we be reaching a critical moment of actually confirming an inherent organic, fertile milieu?

Finding the first generation of metals in the early Universe and identifying their origin is an important goal of modern astrophysics. In regard, we report deep JWST/NIRSpec spectroscopy of a GS-z12 galaxy as the most distant detection of a metal transition and redshift via emission lines. We derive a super-solar carbon-to-oxygen ratio higher than the C/O measured in galaxies discovered by JWST, and higher than Type-II supernovae enrichment. Such a high C/O in a galaxy observed 350 Myr after the Big Bang may be explained by the yields of metal poor stars, and may even be the heritage of the first generation of supernovae from Population III progenitors. (Excerpt)

The appearance of the first galaxies marks a key phase transition of the Universe with the start of stellar nucleosynthesis and the diffusion of metals. Extensive theoretical work has been devoted to predicting the properties of the first generation of stars and their supernova yield. The launch of JWST enabled, for the first time, the measurement of the physical properties of galaxies. These are generally understood in terms of decreasing gas metallicity and increasing density, ionisation parameter, temperature and stochasticity of their star-formation histories. (1)

Animate Cosmos > Organic > quantum CS

Campaio;i, Francesco, et al. Quantum Master Equations: Quantum Optics, Quantum Computing, and Beyond. PRX Quantum. 5/020202, 2024. An entry by RMIT University, Melbourne and University of Padua physicists to exemplify how this once arcane, prohibitive domain has now attained a current facile vernacular which is taught in high schools. See also Hyperdimensional Quantum Factorization by Prathyush Poduval, et al at arXiv:2406.11889 for another instance.

Quantum master equations are an invaluable tool to model the dynamics of a plethora of microscopic systems, ranging from quantum optics and quantum information processing to energy and charge transport, electronic and nuclear spin resonance, photochemistry, and more. This tutorial offers a concise and pedagogical introduction to quantum master equations, accessible to a broad, cross-disciplinary audience. The reader is guided through the basics of quantum dynamics with hands-on examples that increase in complexity. These methods are illustrated with code snippets in python and other languages as a starting point for more sophisticated implementations.

Animate Cosmos > Organic > Biology Physics

, . Hernandez, Edward, et al. Power-law distributions of urban tree cover. Physica A: Statistical Mechanics. 643/129779, 2024.. Physica A: Statistical Mechanics.. 643/129779, 2024. De La Salle University, Manila, Philippines system physicists report an implicate presence of dynamic complexity in effect even across citified greenery. Into these mid-2020s how might we all be able, just in time, to recognize life’s ecosmome to geonome endowment so as to intentionally receive, avail and continue?

Many large-scale systems in nature and society are distinguished by self-organized criticality (SOC), a dynamical state that produces robust power-law statistics without fine-tuned parameters. However, many of these systems are also affected by human activities, leading to the dual action of self-organization and human intervention. In this work, we extract the geographical areas of tree-covered greeneries in an urbanized setting and show the constant emergence of stable power-law distributions which are independent of the specific city. The result shows that while anthropogenic factors influence the natural environment, these occasions still exhibit complex self-organization. (Abstract)

Animate Cosmos > Organic > Biology Physics

Bardella, Giampiero, et al.. Lattice physics approaches for neural neworks.. arXiv:2405.12022. Sapienza University of Rome system physiologists scope out a necessary, obvious trace of our human cerebral faculty beyond neural nets all the way to fundamental sources. As this mid 2020s consilience becomes more evident, prime insights such as renormalization group theory (which is akin to complexity phenomena) can be found to have an integral, structuring affinity.

Modern neuroscience has evolved into a frontier field that draws on novel conceptual frames inspired by physics and complex systems science. In this regard, we introduce a mathematical framework to describe the spatiotemporal systems of neurons using lattice field theory, the reference paradigm for particle physics. We summarize its basic features to show how to readily connect this prime model to experimental variables using well-known renormalization procedures. This synopsis yields key concepts to describe neural networks using lattice physics and to gain generative models underpinned by physical principles. (Excerpt)

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