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Song, Tiancheng, et al. Unconventional Superconducting Quantum Criticality in Monolayer WTe2.. arXiv:2303.06540. Into the mid 2020s, fifteen Princeton University and National Institute for Materials Science and Nanoarchitectonics, Japan researchers proceed to find an inherent tendency for optimum critical behavior even in this substantial realm. See also Self-similarity of the third type in ultra relativistic blastwave by Tamar Faran, et al at arXiv:2402.07978 for another instance of deeply ingrained critical behavior.

The superconductor to metal transition in two dimensions (2D) provides a platform for study quantum phase transitions (QPTs) and critical phenomena but many questions remain. Extending Nernst experiments down to millikelvin temperatures, we identify a superconducting quantum critical point (QCP) in spin Hall insulator made of tungsten ditelluride (WTe2). These findings, which have no prior analogue, call for careful examinations of the mechanism of the QCP, including the possibility of a QPT between ordered phases in the monolayer. Our experiments open a new avenue for studying quantum critical matter. (Abstract)

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

Pierre-Yves Oudeyer. www.pyoudeyer.com.. . The French computational psychologist (search) is the director of the Flowers project-team at the Inria Center of University of Bordeaux. Current (March 2024) projects are now much involved with chatty AI features guided by insights gained from studies with children. A recent talk is Developmental AI: machines that learn like children and help children learn better. As the quotes say, another senior scholar finds evidence that both youngsters and large language modes use trail/error iterate methods in similar ways. See also Open-ended learning and development in machines and humans on the flowers.inria.fr. site.

Together with a great team, I study lifelong autonomous learning, and the self-organization of behavioural, cognitive and language structures at the frontiers of artificial intelligence and cognitive sciences. I use machines as tools to understand better how children learn and develop, and I study how one can build machines that learn autonomously like children, as well as integrate within human cultures, within the new field of developmental artificial intelligence. (P-Y O)

The Flowers project-team, at the University of Bordeaux and at Ensta ParisTech, studies versions of holistic individual development. These models can help us better understand how children learn, as well as to build machines that gain knowledge as children do, aka developmental artificial intelligence, with applications in educational technologies, automated discovery, robotics and human-computer interaction.

Frank, Michael. Baby steps in evaluating the capacities of large language models.. Nature Reviews Psychology. 2/6, 2023. A Stanford University child psychologist offers another recognition that an intrinsic affinity seems to be apparent between such ChatGPT resources and how children achieve literacy and factual comprehension. It is then recommended that an integrative accord between the two general approaches would be beneficial. See also Variability and Consistency in Early Language Learning: The Wordbank Project by MF and colleagues (MIT Press, 2021).

Large language models show remarkable capacities, but it is unclear what abstractions support their behaviour. Methods from developmental psychology can help researchers to understand the representations used by these models, complementing standard computational approaches — and perhaps leading to insights about the nature of mind.

Levi, DeHaan. LLM as Child Analogy.. levidehaan.com.. This is a posting by a veteran cyber designer whose group projects can be found on the above site. A longer title is Theorem: Evolutionary Pathway of LLMs under the "LLM as Child Analogy" which may be reached by Google keywords. We cite some excerpts which are similar to Marina Pantcheva’s views herein.

LLMs: A machine learning model designed to process and generate human-like text based on statistical patterns in data. Real-time Adaptability: The ability to modify its behavior based on new information. Memory Retrieval: A system to store, recall, and utilize past interactions. Decision-making Algorithm: A set of rules to make choices. Creative Reasoning: The capability to generate original content but not confined to it.

Children possess real-time adaptability, have a memory retrieval system. develop decision-making abilities and the capability for creative reasoning. If LLMs are to evolve along the lines of children, then the first logical step would be to implement real-time learning algorithms, moving from static to dynamic models. For LLMs to be more analogous to children, they would need the ability to generate new, original content, potentially through some form of creative reasoning. Achieving real-time adaptability would make LLMs dynamic learners, thereby aligning with human children.

Pantcheva, Marina. How do LLMs and humans differ in the way they learn and use language.. rws.com/blog/large-language-models-humans.. A Senior Group Manager at RWS (see below) with a PhD in Theoretical Linguistics addresses this aspect with a list of several ways by which youngsters become talkative and informed. She then makes note of a general affinity between these personal learning methods and the algorithmic, iterative processes that form LLMs content and capabilities.

The question of how children learn language is central to modern linguistics. Numerous contributions have sought to explain this process, here are a few:

Social interactionist theory suggests that feedback and corrections play a pivotal role in language acquisition along with dialogue between the child and the linguistic adults.
Behaviorist theory posits that children learn language by mimicking those around them and positive reinforcement for their endeavors.

Statistical learning theory proposes that children use the natural statistical properties of language to deduce its deep structure such as sound patterns, words, and grammar.
Universal grammar theory argues for the existence of constraints on what human language can look like. In essence, children possess an innate biological component that enables their rapid development of language. (MP)

Genuine Intelligence (GI). Generative AI and Large Language Models are redefining the boundaries of language and content transformation. GI is not just about AI and people working together, it composes a symbiotic blend of AI's computational capacity with human insight and creativity. RWS is a global company based in the UK for transforming content through translation, localization and AI technology blended with human expertise.

Ruggeri, Azzurra, et al. Preschoolers search longer when there is more information to be gained. Developmental Science. 27/1, 2024. Senior psychologists AR, MPI Human Development, Oana Stanciu, Central European University, Madeline Pelz, MIT, Alison Gopnik, UC Berkeley and Eric Schulz, MPI Biological Cybernetics provide new insights into how children proactively seek and acquire knowledge and then recommend that the process would serve Large Language Models if it was written into its algorithms

What drives children to explore and learn when external rewards are uncertain or absent? We tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24–56-month-olds' behavior in a game where they had to search for an object with uncertainty about which specific object was hidden. We found that children were more persistent in their search when there was higher ambiguity and more information to be gained. Our results highlight the importance of artificial intelligence research to invest in curiosity-driven algorithms. (Abstract)

All in all, these findings consolidate our understandings of children’s motivation to learn and explore, and have strong implications for developmental psychology and artificial intelligence. The results are consistent with a theory of children’s exploration and learning driven by uncertainty reduction. From an artificial intelligence view, they lend further support to the idea that to build computational machines that learn like children, one should build curiosity-based systems and design algorithms motivated by the underlying expected IG (Intelligence gain) of their actions. (6)

Stevenson, Claire, et al. Do large language models solve verbal analogies like children do?. arXiv:2310.20384. University of Amsterdam psychologists including Ekaterina Shutova cite another present recognition of a basic correspondence, in this title case, of how youngsters draw on commonalities and associations between items or situations and what it seems these AI chatBot procedures arealso trying to do.

Analogy-making lies at the heart of human cognition. Adults solve analogies such as horse to stable and chicken to coop. In contrast, children use association, and answer egg. This paper investigates whether large language models (LLMs) can solve verbal analogies in A:B::C form, similar to what children do. We use analogies from an online learning environment, where 14,002 7-12 year-olds from the Netherlands solved 622 analogies in Dutch. We conclude that the LLMs we tested indeed tend to solve verbal analogies by association like children do. (Excerpt)

An important take-away from our study is that LLMs may solve analogies as well as 11 year-olds, but to ascertain whether this reasoning is emerging in these systems we need to know the mechanisms by which they obtain these comparisons. Our findings point towards associative processes in play, perhaps similar to those in children. (11)

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

Hamilton, Chris and Jean-Baptiste Fouvry.. Kinetic Theory of Stellar Systems. arXiv:2402.13322. IAS, Princeton and Sorbonne University astrophysicists contribute a 66 page, 182 reference Tutorial as a latest statement of the dynamic sunny stars. Nine segments such as Orbits in mean field potentials well covers the technical content.

Stellar systems - star clusters, galaxies, dark matter haloes, and so on - are ubiquitous characters in the evolutionary tale of our Universe. This tutorial article is an introduction to the collective dynamical evolution of the very large numbers of stars and/or other self-gravitating objects that comprise such systems, i.e. their kinetic theory.

Saarloos, Win van, et al. Soft Matter: Concepts, Phenomena, and Applications. Princeton: Princeton University Press, 2024. Wim van Saarloos is professor emeritus of theoretical physics at the Lorentz Institute at Leiden University, Vincenzo Vitelli is professor of physics at the University of Chicago and Zorana Zeravcic is professor of physics in the Gulliver Laboratory at ESPCI Paris. In regard they contribute the first book treatment of this animate subject, hardly a decade old. A chapter on Active Matter is included along Non-Equilibrium Pattern Formation, Elasticity, Designing Matter and so on. Altogether one more perspective upon a natural dynamic liveliness due to common codings gains a broad and deep expression.

Soft matter science is an interdisciplinary field at the interface of physics, biology, chemistry, engineering, and materials science. It encompasses colloids, polymers, and liquid crystals as well as rapidly emerging topics such as metamaterials, memory formation and learning in matter, bioactive systems, and artificial life.. The presentation integrates statistical mechanics, dynamical systems, and hydrodynamic approaches with conservation laws and broken symmetries as guiding principles along with computational and machine learning advances.

Wang, Jai, et al. Interstellar formation of glyceric acid, the simplest sugar.. Science Advances. March 24, 2024. University of Hawaii and University of Mississippi (Ryan Fortenberry) cite their sweet detection of this organic mainstay compound. As the quotes imply, once again nature’s astrochemistry seems to possess an innate spontaneity to form just what life needs for the long cellular ovogenesis to our late retrospect description.

Glyceric acid [HOCH2CH(OH)COOH] is a key molecule in biochemical metabolic processes such as glycolysis. Although linked to the origins of life and identified in carbonaceous meteorites, the mechanisms of its formation have remained elusive. Here, we report the first abiotic synthesis of racemic glyceric acid via the radical-radical reaction of the hydroxycarbonyl radical with 1,2-dihydroxyethyl radical in low-temperature carbon dioxide and ethylene glycol ices. This work reveals the key pathways for glyceric acid synthesis through nonequilibrium reactions from profuse precursor molecules, advancing our fundamental knowledge of the formation of key biorelevant organics—sugar acids—in deep space. (Abstract)

Here, we demonstrate the very first abiotic synthesis of 1 in low-temperature (5 K) carbon dioxide and ethylene glycol (HOCH2CH2OH, 16) ice mixtures. This was accomplished via the barrierless radical- radical eaction of the hydroxycarbonyl (HOĊO, 11) with the 1,2-dihydroxyethyl (HOĊHCH2OH, 17) radicals (Figs. 1 and 2). These model ices were exposed to energetic electrons mimicking secondary electrons generated in the track of galactic cosmic rays (GCRs) pene-trating ices in cold molecular clouds aged a few million years. (1)

Ziurys, Lucy. Prebiotic Astrochemistry from Astronomical Observations and Laboratory Spectroscopy. Annual Review of Physical Chemistry. Volume 75, 2024. As the quote notes, a senior University of Arizona bioastronomer contends that the profuse ISM population of appropriate biomolecule precursors found so far must have made a vital contribution to the origin and occurrence of nascent Earth life and evolution. See also RNA-catalyzed evolution of catalytic RNA by Nikolaos Papastavrou, et al in PNAS (121/11, 2024) and Complex organic molecules uncover deeply embedded precursors of hot cores by Laure Bouscasse, et al at arXiv:2403.05237 for more evidence of a natural life-bearing spontaneity. Altogether these findings suggest that our worldwise scientific quest may have at last reached an actual realization of a phenomenal ecosmic fertility which proceeds with its own procreative development.

The discovery of more than 200 gas-phase chemical compounds in interstellar space has led to the speculation that this nonterrestrial synthesis may play a role in the origin of life. Interstellar chemistry produces a wide range of organic molecules in dense clouds such as NH2COCH3, CH3OCH3, CH3COOCH3, and CH2(OH)CHO. Elusive phosphorus has now been found in molecular milieu and the sites of star formation. The presence of fertile interstellar starting material, as well as the link to planetary bodies such as meteorites and comets, suggests that astrochemical processes set a prebiotic foundation. (Abstract)

Kaib, Nathan and Sean Raymond. Passing Stars as an Important Driver of Paleoclimate and the Solar System's Orbital Evolution. Astrophysical Journal Letters. 962/2, 2024. Planetary Science Institute, Tucson and University of Bourdeaux astrophysicists (search SR) are now able to add another ISM factor which could have had an effect on Earth life evolution. As the title and quotes say, interstellar traffic could brush by and influence atmospheric conditions long ago.

Reconstructions of the paleoclimate indicate that ancient climatic fluctuations on Earth are often correlated with variations in its orbital elements. However, the chaos inherent in the solar system's evolution prevents numerical simulations from predicting Earth's past orbits beyond 50–100 Myr. Here we present simulations that include the Sun's nearby stellar population, and find that close-passing stars alter our entire planetary system's orbital history via gravitational perturbations of the giant planets. (Excerpt)
We show that stellar encounters play an important role in our solar system’s long-term dynamical evolution. First, stellar encounters significantly accelerate the chaotic diffusion of Earth’s orbit, from their perturbations to the giant planets’ orbit.. Although it takes tens of Myrs for the effects of stellar passages to significantly manifest themselves, the long-term orbital evolution of the Earth and the rest of the planets is linked to these stars. (9)

Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

Jensen, Henrik. Complexity Science: The Study of Emergence. Cambridge. UK: Cambridge University Press, 2023.. Cambridge. UK: Cambridge University Press, 2023. The Imperial College London mathematician (search) writes a latest comprehensive textbook for this nascent 21st century study of our actual lively, anatomic, physiological, procreativity. Its contents course from first theoretic principles to statistical mechanics, networks, information, much more and onto critical transitions and tipping points.

Rosas, Fernando, et al.. Software in the natural world: A computational approach to emergence in complex multi-level systems. arXiv:2402.09090. University of Sussex, Imperial College London (Pedro Mediano), Graz University of Technology, Austria, McGill University (Anil Seth), University of Hertfordshire, and EPFL, Lausanne propose to cross-combine nonlinear complexity phenomena with mathematical program procedures as a beneficial way to achieve a complete, effective integration.

Understanding the functional architecture of complex systems is crucial to reveal their inner workings and enable prediction and control. Here we develop a computational approach to study emergent macroscopic processes by way of a mathematical formalism that can express self-contained informational, interventional properties. Our method forms a hierarchy of nested self-contained processes from the statistical physics and computational neuroscience literature wherein holistic processes are akin to software-like. Overall, this framework enables a deeper understanding of multi-level complex systems so they can be better simulated, predicted, and controlled. (Abstract edit)

Lalli, Margherita and Diego Gariaschelli. Geometry-free renormalization of directed networks: scale-invariance and reciprocity. arXiv:2403.00235. IMT School for Advanced Studies, Lucca, Italy physicists are able to demonstrate an effective integrity of this physical attribute with multiplex phenomena across diverse, practical instances. See also Renormalization of Complex Networks with Partition Functions by Jung, Sungwon, et al at arXiv:2403.07402

Recent research has tried to extend the concept of renormalization to more general networks with arbitrary topology. Here we show that the Scale-Invariant Model can be extended to directed networks without an embedding geometry or Laplacian structure. Moreover, it can account for the tendency of links to occur in mutual pairs more or less often than predicted by chance. By way of renormalization rules, we propose a multiscale international trade network with nontrivial reciprocity and an annealed model where positive reciprocity emerges spontaneously. (Excerpt)

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