Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 1 through 15 of 59 found.
The Genesis Vision > Historic Precedents
Complexity, Universal Libraries, DNA Sequences.
Chaos, Solitons and Fractals.
In 2020, I came across a photocopy of this extraordinary article from the Boston College Library. Two decades into this sapiensphere century, it is now fully online as a good example of this worldwise advance. The physicist author (1923-2005) had a notable career (Wikipedia) as chief scientist for the Rand Corporation, along with contributions to physical theories. Here it is observed that many aspects of the 1990s computational frontier such as Turing machines, cellular automata, formal languages, notational neural nets, dynamical systems and algorithm information theory imply and could at last confirm the presence of an independent mathematical domain which underlies and guides this emergent existence.
The paper goes on to say that these approaches might fulfill a traditional inklings of a textual milieu seen as a natural library. Abraham Fraenkel’s Abstract Set Theory and especially Jorge Borges’ short story The Library of Babel are cited. Bruno A. adds a programmic version in the form of ‘normal number’ (Google) codes. With this in place, DNA biomolecules are reviewed as a prime analogic instance. With whole genome sequencings just underway, these efforts are predicted to have a deep affinity with library-like qualities. Further occasions are noted for the immune system and neural net brains. And again into the 2020s whomever in a revolutionary ecosmic genesis are we peoples to become ordained readers and cocreative writers?
Complexity studies are burgeoning into an ever-increasing number of fields. This paper seeks to abstract from many non-biological complexity areas some exemplary representatives. One such common thread leads to the notion of a Universal Library containing all possible texts and, correspondingly, all possible knowledge. This notion is then wedded to an elementary number theory to indicate where replicas of universal libraries exist, with certain attributes. Next, a prime example of a biological complexity - DNA sequences - is introduced. While DNA is often termed a library specifying the heritability of individuals and species, this paper explores whether relations exist between DNA sequences and universal libraries to test the initially identified complexity thread to link non-biological and biological areas. (Abstract)
The Genesis Vision > Current Vistas
It seems fair to conclude from these brief comments that there are significant and marked similarities between features of ULNN (Universal Library Normal Numbers) and features of the finite DNA sequence in a genome and as well where the genome seems to borrow from a much larger DNA sequence. In effect, we have come full circle. We have introduced a biological complexity area - the finite DNA sequence of the human genome - and have shown how this area also reflects many aspects of ULNN and hence has ties to the original non-biological complexity areas, i.e., we have here one link between life and non-life. (970-971)
Analogia: The Emergence of Technology beyond Programmable Control.
New York: Farrar, Straus and Giroux,
The polycultural sage, at home in both tradition and science, writes another a unique, insightful contribution. Its timely theme courses from Gottfried Leibniz to 1950s mathematic computations at the Institute for Advanced Studies at Princeton where his father, Freeman was posted, and onto the current algorithmic Internet. By this vista, the innate presence of two discrete digital and integral analogue modes can be well discerned. So to say, this natural realm which our human intellect has long tried to comprehend is now found to be graced by such particle/wave, node/link apart/together, serial/spatial, me/We archetypes. By this view, one could infer, as the Civilization section does, that indigenous peoples abided in an analog milieu.
On a personal note, in 2005 I was paired with Freeman Dyson as a speaker (slides on home page for slides) so to attempt a 21st century “natural philosophia,” which he says is vital to recover today. (search FD). For this review, while George D. closes with a concern that a worldwide AI analogic phase bodes to take over, his 2020 witness of a universal reality which is deeply distinguished by an interactivity of these informational states could advise a salutary resolve by way of their complementary unity. (As I write this in late August, our American land is being devasted by their polar opposition.)
A Learning Planet > The Spiral of Science
George Dyson is an independent historian of technology whose works have included the Aleut kayak (Baidarka, 1986), the evolution of artificial intelligence (Darwin Among the Machines, 1997) and the transition from numbers that mean things to numbers that do things (Turing’s Cathedral, 2012).
In 1716, the philosopher and mathematician Gottfried Wilhelm Leibniz spent eight days with Peter the Great in Saxony, seeking to initiate a digitally-computed takeover of the world. In his Darwin Among the Machines (1997) and Turing’s Cathedral (2012), Dyson chronicled the mid 20th century realization of Leibniz’s dream by a series of iconoclasts who brought his ideas to life. In his pathbreaking new book, Analogia, he chronicles the people who fought for the other side―the Native American leader Geronimo and physicist Leo Szilard, among them―by vignettes that will change our view not only of the past. The convergence of this historical archaeology with Dyson’s personal story - in Princeton frontier physics and computer science and the rainforest of the Northwest Coast - leads to a prophetic vision of an analog revolution already under way.
Nature uses digital coding, embodied in strings of DNA, for the storage, replication, and modification of instructions conveyed from one generation to the next, but relies on analog coding and computing, embodied in brains and nervous systems, for real-time intelligence and control. Coded sequences of nucleotides store the instructions to grow a brain, but the brain itself does not operate like a digital computer by storing and processing digital code. (6) In a digital computer, one thing happens at a time. In an analog computer everything happens at once. Brains process three-dimensional maps continuously, instead of one-dimensional algorithms step by step. Information is pulse-frequency coded in the topology of what connects where, dot digitally coded by precise sequences of logical events. (6)
There is a corollary to the continuum hypothesis concerning computation among living and non living things. Computers, like Cantor’s infinities, can be divided into two kinds. Digital computers are finite but unbounded discrete-state machines whose possible states can be mapped in one-to-one correspondence to the integers. Analog computers, lacking discrete states that can be mapped directly to the integers, belong instead to some subset of the continuum, with every such subset having the power of the whole. Digital computers deal with integers, binary sequences, deterministic logic and time that is idealized into discrete increments. Analog computers deal with real numbers, nondeterministic logic, and continuous functions, including time. (247-248)
Howell, Owen, et al.
Machine Learning as Ecology.
Journal of Statistical Physics.
In a Machine Learning and Statistical Physics section, Boston University and Boston College physicists including Pankaj Mehta scope out a newly evident affinity between these novel computational methods and natural ecosystem activities. By technical finesses, parallels are found to occur by way of common “algorithmic” processes. An informative cross-transfer from each field builds the case which then reveals a universality from cognitive to flora/fauna to physical phases as they become a fertile ground.
Machine learning methods have had spectacular success on numerous problems. Here we show that a prominent class of learning algorithms, aka support vector machines (SVM), have a natural interpretation in terms of ecological dynamics. We use these ideas to design new online SVM algorithms that exploit ecological invasions, and benchmark performance using the MNIST dataset. Our work provides a new ecological lens through which we can view statistical learning and opens the possibility of designing ecosystems for machine learning. (Abstract)
A Learning Planet > The Spiral of Science
Support Vector Machines is a mathematical method used for classification and regression problems. It can solve linear and non-linear practical applications. Its operative algorithm creates a line or a hyperplane which separates the data into classes.
The Evolution of Knowledge: Rethinking Science for the Anthropocene.
Princeton: Princeton University Press,
The MPI for the History of Science director publishes a collegial volume some 25 years in the making that from our late vantage achieves a fresh, integral surmise. Human history can now appear as a grand knowledge gaining project from Greece, China, and Europe to its present Anthropic worldwide transition. By such a vista, and in accord with this website, into the 21st century an epochal shift is much underway from individuals (men) and local groups to a “global learning process” (21) in the form of a collective, cumulative repository in its online noosphere (re V. Vernadsky and P. Teilhard). As we try to broach here, a new phase of guided facilitation so as to seek ways to better organize, translate and foster accessible usage. A detailed glossary with sections such as Cognitive Psychology and Science, Complex Systems Theory, Earth Systems, Epistemic Networks, and Knowledge Development then provides an expansive guide.
This book presents a new perspective about the history of science and technology, one that offers a grand narrative in which knowledge serves as a critical factor of cultural evolution. It examines the role of knowledge in global transformations going back to the dawn of civilization all the way to complex challenges confronting us today in the Anthropocene epoch shaped by humankind. Renn reframes the history of science and technology, analyzing key episodes such as the evolution of writing, the Scientific Revolution of early modernity, and the current digital globalization of scientific findings. (Publisher)
A Learning Planet > The Spiral of Science
In chapter 13, we saw how epistemic communities may come into being by processes of self-organization involving cognitive networks. Clearly, even in its current form, the Web has immensely improved the conditions for such self-organizing networks. The challenges of the Anthropocene might act as a catalyst for the emergence of a global epistemic community beyond disciplinary trenches, for refocusing the Web on problems of knowledge, and for creating new bridges between the academic world and civil society. (408)
Epistemic Evolution: A process emerging from cultural evolution in which the knowledge economy of science has transformed from an accidental into a necessary condition for preserving, sharing, and developing the achievements of cultural evolution, and possibly even the survival of the human species on a global scale. (Glossary)
Schutt, Kristof, et al, eds.
Machine Learning Meets Quantum Physics.
The six editors of meeting papers about this auspicious synthesis are from central Europe and Japan. Some articles are Kernel Methods for Quantum Chemistry, Neural Networks, Atomic Scale Properties based on Physical Principles, Physical Extrapolation of Quantum Observables and Deep Learning of Atomistic Representations. While a 20th century quantum version is still an arcane mystery, into the 21st century this deepest domain is now amenable to macro-classical phase neural network analysis and operation. In a philoSophia view, composite human agency indeed seems made, empowered and meant to take up a new ecosmic cocreation going forward.
Designing new molecules and materials requires the ability to calculate microscopic properties such as energies, forces and electrostatic multipoles, as well as forming macroscopic qualities. A way to do this is by first-principle calculations rooted in quantum and statistical mechanics, they come with a high computational cost. To overcome this, there have been increased efforts to enhance quantum simulations with machine learning (ML) techniques. This book emerged from a series of workshops so to give a snapshot of this rapidly developing field. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary for a broader scientific context.
A Learning Planet > The Spiral of Science > deep
Tzachor, Asaf, et al.
Artificial Intelligence in a Crisis Needs Ethics with Urgency.
Nature Machine Intelligence.
Cambridge University, Center for the Study of Existential Risk and Center for the Future of Intelligence scholars weigh in by saying that while the COVID pandemic can be well studied by AI to better analyze spreadings, track movements and so on, its use needs to be scrutinized and guided by respectful methods.
Artificial intelligence tools can help save lives in a pandemic. However, the need to implement technological solutions rapidly leads to challenging ethical issues. We need new approaches for ethics with urgency, to ensure AI can be safely and beneficially used in the COVID-19 response and beyond. (Abstract)
A Learning Planet > Mindkind Knowledge
Heersmink, Richard and John Sutton.
. Cognition and the Web: Extended, Transactive, or Scaffolded?
Erkenntnis: An International Journal of Scientific Philosophy.
In this European journal whose title means “understanding, realization, knowledge,” La Trobe University and Macquarie University philosophers scope out various ways that an individual web user and the global Google repository which is being interactively viewed might be seen as a novel wider representative phase of our cerebral domain. In such regard, here is another appreciation of how a person’s sapience can and does in fact expand beyond the biological brain itself.
In the history of external information systems, the World Wide Web presents a significant change in terms of the accessibility and amount of available information. Constant access to various kinds of online information affects the way we think, act and remember. Cognitive scientists have started to examine the interactions between the human mind and the Web, mainly how online information influences our biological memory. We use concepts from extended and distributed cognition frameworks and from transactive memory theory to analyse such an inter-relation. (Abstract)
A Learning Planet > Mindkind Knowledge
Global Brain: Foundations of a Distributed Singularity.
Korotayev, Andrey and David LePoire, eds.
The 21st Century Singularity and Global Futures.
International: Springer, 2019.
A Bertalanffy Center for the Study of Systems Science, Vienna scholar achieves a well researched, thoughtful essay upon the emergent formation of an informational worldwise phase of collective, informed intelligence. It is proposed that this evident presence appears to have a capability to gain actual knowledge by its own analogous cognizance. In regard, if this spherical sapience can be rightly identified, enhanced and availed, it could provide a vital resource to advise, edify and solve dire problems which are otherwise intractable. See also the author’s 2020 book Global Brain Singularity (Springer) which is his doctoral thesis at the Free University of Brussels with Francis Heylighen.
Global Brain is a concept used to describe and understand the distributed, self-organizing intelligence currently emerging from all people and information-communication technologies (ICT) connected via the Internet. In its future network form it could become more intelligent and coherent with the capability to coordinate the functional operations of human civilization. Such a system would represent a new level of organized complexity which would allow people to deal with planetary problems that cannot be solved by contemporary methods. Thus, in a Global Brain metasystem, the human possibility space would open up levels of freedom and opportunity which have never before existed in evolutionary history. (Abstract)
A Learning Planet > Mindkind Knowledge
“Global Brain” is a helpful metaphor to understand how our modern human society has become mediated by Internet functions like a biological brain. Here we posit that as brains produce intelligence, goal-directedness, and consciousness, so our species as a whole civilization produces higher order intelligence, goal-directedness, and consciousness. In positive regard, a Global Brain would help the human superorganism solve problems too complex for any lower level of intelligent organization. In another way, neurons within neural networks process information in a parallel and distributed fashion transmitting information; this is the same basic structural pattern used by humans to transmit information via the Internet. (3, edits)
Therefore, the Global Brain may be a useful metaphor for describing a distributed and self-organizing planetary superintelligence emerging from humans and ICT interacting and learning via the Internet. (4) But importantly for our inquiry, the idea of the Earth itself as a superorganism asks us to reflect on the possibility that the Global Brain would function as the structure of a nervous system. Thus, just as animals grew increasingly sophisticated brains so that they could make better models of the world and eventually their own models (self-consciousness), the Earth could be forming a brain so that it can accurately model its surrounding environment (i.e., the universe). (5)
Liu, Wenyuan, et al.
Predicting the Evolution of Physics Research from a Complex Network Perspective.
We cite this entry by Nanyang Technological University, Singapore and Wroclaw University of Science, Poland computational intelligence researchers because it considers that the process of cumulative scientific inquiry and knowledge, which presently proceeds on a global scale, can be seen to exhibit and be treatable by the same dynamic multiplex networks as everywhere else. Here then is another way and reason to appreciate a planetary learning achievement due to humankinder altogether as it goes forth by itself. See also Knowledge Evolution in Physics Research: An Analysis of Bibliographic Coupling Networks by Wenyuan Liu, et al in PLOS One (September 2017). All of which quite accords with the intent of this Annotated Anthology website.
The advancement of science, as outlined by Popper and Kuhn, is largely qualitative, but with bibliometric data, it is possible to develop a quantitative picture of scientific progress. In this paper, we address this problem of quantitative knowledge evolution by analyzing the APS data sets from 1981 to 2010. We build the bibliographic coupling and co-citation networks to detect topical clusters (TCs), measure the similarity of TCs, and visualize the results as alluvial diagrams. We found the number of papers from certain journals, the degree, closeness, and betweenness to be the most predictive features. Our results represent the first step from a descriptive understanding of the science of science (SciSci), towards one that is ultimately prescriptive. (Abstract excerpt)
Animate Cosmos > Quantum Cosmology
Conzinu, Pedro, et al.
Primordial Black Holes from Pre-Big Bang Inflation.
Journal of Cosmology and Astroparticle Physics.
We enter this posting by University of Pisa and Bari physicists as an instance of worldwide online collaborations which are now able to explore, hypothesize and quantify, so it seems, across any spatial and temporal expanse. In 2020 regard, whom might we microcosmic collaborative peoples altogether be to span and learn about such universal breadth and depth? See also, for example, The Self-Tuning of the Cosmological Constant at arXiv:2001.05510. By a philoSophia view, could it be imagined that an ecosmic genesis is trying to self-recognize and pass its operational knowledge onto our Earthkinder agency for a future cocreativity.
We discuss the possibility of producing a significant fraction of dark matter in the form of primordial black holes in the context of the pre-big bang inflationary scenario. We take into account, to this purpose, the enhancement of curvature perturbations possibly induced by a variation of the sound-speed parameter during the string phase of high-curvature inflation. After imposing observational constraints, we find that the considered class of models is compatible with the production of a large amount of primordial black holes in the mass range relevant to dark matter. (Abstract)
Animate Cosmos > Quantum Cosmology > cosmos
Let us finally recall that, in the string cosmology scenario that we have considered, the collapse of primordial inhomogeneities leading to PBH formation can be associated with perturbation modes re-entering the horizon either in the radiation- or in the axion-dominated regime of post-inflationary evolution. In the second case, corresponding to a dust-dominated epoch, it turns out that the spectral constraints determining a significant PBH production might be somewhat relaxed with respect to the one used in this paper. (23)
IAU Strategic Plan 2020-2030.
This is a 72 page International Astronomical Union document drafted by Debra Elmegreen, Ewine van Dishoeck, Renée Kraan-Korteweg and Piero Benvenuti to scope out a range of activities for new research projects and proposals, along with public and educational communication and engagement. Founded in 1919, the IAU publishes Symposia Proceedings of which the latest volume 353 is Galactic Dynamics in the Era of Large Surveys, see also Origins: From the Protosun to the First Steps of Life (345).
The International Astronomical Union, whose mission is to promote and safeguard astronomy in all its aspects through international cooperation, has been the worldwide organisation of professional astronomers since 1919. In the last century, the endeavour of astronomy has grown and evolved in ways that could not have been anticipated or predicted at the time of the IAU’s founding. In the early 1900s, astronomers had not yet proven that there were other galaxies besides the Milky Way. The expansion of the Universe was unknown IAU Strategic Plan 2020 –2030. (8)
Animate Cosmos > Quantum Cosmology > Gaia
Now, a century later, we know that the Universe is teeming with planets beyond our Solar System; thousands have already been discovered. Supermassive black holes reside in the centres of massive galaxies, and manifest themselves as quasars in the early Universe. Nucleosynthesis is understood to fuel stars. The accelerating Universe is filled with dark energy and dark matter, and the baryonic matter of which we are made. Gravitational waves reach us following black hole and neutron star mergers. We are poised to be able to answer the age-old questions of our place in the Universe and whether or not we are alone. (9)
Lenton, Timothy, et al.
Life on Earth is Hard to Spot.
Gaia advocates TL, University of Exeter, Sebastien Dutreuil, University of Aix-Marseille, and Bruno Latour, Sciences Po, France note the long last acceptance of James Lovelock’s biospheric self-regulation over evolutionary spans by life’s composite vitalities. But this organic essence, here noted with a capital L, is not immediately evident. A teleology issue also needs to be clarified, which perturbs R. Dawkins, but overall a 2020 vision of a habitable bioworld is now well in place as evinced by its practical utility for Earth systems scientists.
The triumph of the Gaia hypothesis was to spot the extraordinary influence of Life on the Earth. ‘Life’ is the clade including all extant living beings, as distinct from ‘life’ the class of properties common to all living beings. ‘Gaia’ is Life plus its effects on habitability. Life’s influence on the Earth was hard to spot for several reasons: biologists missed it because they focused on life not Life; climatologists missed it because Life is hard to see in the Earth’s energy balance; Earth system scientists opted instead for abiotic or human-centred approaches to the Earth system; Scientists in general were repelled by teleological views that Life acts to maintain viable conditions. Instead, we reason from organisms’ metabolisms outwards, showing how Life’s coupling to its environment has led to profound effects on Earth’s biosphere. (Abstract)
Animate Cosmos > Quantum Cosmology > Gaia
Steffen, Will, et al.
The Emergence and Evolution of Earth System Science.
Nature Reviews Earth & Environment.
In this inaugural issue of a new Nature journal, eight veteran Earth scientists including Jane Lubchenco, Hans Schellnhuber, and Tim Lenton provide a status report from V. Vernadsky’s biosphere to J. Lovelock’s Gaia alive model and onto current needs to foster an ecosphere vitality. See also Genealogies of Earth System Thinking by Giulia Rispoli in the same issue.
Earth System Science (ESS) is an emerging transdisciplinary endeavour aimed at appreciating the structure and function of the Earth as a complex, adaptive system. Here, we discuss this integral merit of ESS, and it’s value for understanding global change. Inspired by early work on biosphere–geosphere interactions and by novel perspectives such as the Gaia hypothesis, ESS emerged in the 1980s to meet the need for a new ‘science of the Earth’. ESS has produced new concepts and frameworks which much serve environmental issues, such as the Anthropocene phase, tipping points and planetary boundaries. Moving forward, the grand challenge for ESS is to integrate biophysical processes with populous human dynamics to attain a truly unified vision of the Earth System. (Abstract)
Animate Cosmos > Quantum Cosmology > quantum CS
Bharti, Kishor, et al.
Machine Learning Meets Quantum Foundations.
AVS Quantum Science.
Centre for Quantum Technologies, National University of Singapore physicists including Vlatko Vedral survey the many ways that versatile neural network AI methods have become useful for entanglement, contextuality, nonlocality and other quantum studies. Our further interest is to wonder that as these dynamic topologies become adaptable for so many areas outside a brain, could it imply an actual cerebral essence for the whole ecosmos?
The goal of machine learning is to facilitate a computer to execute a specific task without explicit instruction by an external party. Quantum foundations seek to explain the conceptual and mathematical edifice of quantum theory. Recently, ideas from machine learning have successfully been applied to different problems in quantum foundations. Here, the authors compile the representative works done so far at the interface of machine learning and quantum foundations. (Abstract)
Animate Cosmos > Organic > Biology Physics
Fate of Duplicated Neural Structures.
The Barcelona systems theorist is presently a postdoc at MIT’s Center for Brains Minds + Machines (search LS and visit the CBMM site). After prior collaborations with Ricard Sole (see arXiv site) and others, he continues his project to give life’s evolutionary biology and cognition a deeper statistical and computational physics basis, as it necessarily has to have. His innovative 2020 entry is a good instance of this scientific frontier as it seeks to quantify and join human and universe into a unified organic genesis. Its sections course through bilateral hemispheres, reactive and/or predictive brains, cortical columns, active algorithms, linguistics and more as each form and move by an energetic flow. The 193 references over the 2000s and 2010s document a 21st century worldwise revolution from everything in pieces to altogether now. So this panicky year seems also a time of historic local, global and ecosmic synthesis which, if we could witness, read and avail might help mitigate and guide.
Statistical mechanics determines the abundance of different arrangements of matter depending on cost-benefit balances. Its formalism percolates throughout biological processes and set limits to effective computation. Under specific conditions, self-replicating and computationally complex patterns become favored which yields life, cognition, and Darwinian evolution. Neurons and neural circuits then reside between statistical mechanics, computation, and cognitively in natural selection. A statistical physics theory of neural circuits would tell what kinds of brains to expect under set energetic, evolutionary, and computational conditions.
With this big picture in mind, we focus on the fate of duplicated neural circuits. We look at central nervous systems with a stress on computational thresholds that might prompt this redundancy and at duplicated circuits for complex phenotypes. From this we derive phase diagrams and transitions between single and duplicated circuits, which constrain evolutionary paths that lead to complex cognition. Similar phase diagrams and transitions might constrain internal connectivity patterns of neural circuits at large. Thus the formalism of statistical mechanics seems a natural framework for this promising line of research. (Abstract)