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

C. Earth Learns: Interactive Person/Planet, Self-Organizing, Daily Collaboratiions

Yassini, Rouzbeh. Planet Broadband. Indianapolis: Cisco Press, 2003. Yes, a book from Cisco Systems which along with some hype shows how a “high-speed, always-on connectivity to an interactive digital network” is facilitating a global sphere of ubiquitous communication, information and accessible knowledge.

Yong, Tao and Didier Sornette. Emerging Social Brain: A Collective Self-Motivated Boltzmann Machine. Chaos, Solitons and Fractals. 143/February, 2021. A Southwest University, Chongqing, China scholar and the veteran ETH Zurich systems economist consider ways that cerebral and cognitive qualities could be seen as presently forming out of a range of human activities. See also Life as a Self-Referential Deep Learning System by Yong Tao also in Biosystems (February 2021).

Boltzmann machines are unsupervised-learning neural networks, which have contributed to deep learning architectures. Theoretically, we show that the emergence of a Boltzmann-like income distribution in a society of optimizing agents reflects the spontaneous organization of a human society wherein each person plays a role analogous to that of a neuron within a brain-like architecture. Empirically, we investigate the household income data from free-market countries and find that the income structure for low and middle classes holds to a Boltzmann-like distribution. We thus suggest that social networks are going through a critical evolution to a kind of brain-like structure. (Abstract excerpt)

Yook, Soon-Hyung, et al. Modeling the Internet’s Large-Scale Topology. Proceedings of the National Academy of Sciences. 99/13382, 2002. By means of the application of universal, scale-free network principles.

In contrast with the random placement of nodes, we find that the Internet develops on a fractal support, driven by the fractal nature of population patterns around the world. (13382)

Zak, Michail. From Collective Mind to Communication. Complex Systems. 14/4, 2003. A member of the Ultra-computing Group of the California Institute of Technology proposes a “mathematical formalism” to convey how “natural or artificial living systems” lead to the formation of collective cognitive abilities.

“Collective mind” is introduced as a set of simple intelligent unity (say, neurons, or interacting agents) that can communicate by exchanging information without explicit global control. The concept of “collective mind” has appeared recently as a subject of intensive scientific discussion from economical, social, ecological, and computational viewpoints. (335) Thus, the proposed model offers a unified description of the progressive evolution of living systems, and it reconciles this evolution with the second law of thermodynamics. (351)

Zhong, Ning, et al. In Search of the Wisdom Web. Computer. November, 2002. An introduction to nine papers that explore how the World Wide Web is evolving into an intelligent, socially relevant resource.

The intelligent Web seeks to provide resources that encourage sustainable knowledge creation and scientific and social evolution. (30)

Zhong, Ning, et al, eds. Web Intelligence. Berlin: Springer, 2003. Reports on many different projects to provide the World Wide Web with greater capacities for interactive response and utility.

Zhong, Nong, et al, eds. Web Intelligence Meets Brain Informatics. Berlin: Springer, 2007. With Weibo Gong above, considerations of the intensifying convergence between neuroscience and the worldwide computer web, which, as we realize how truly like a brain it is, such attributes as listed below ought to be further enhanced.

Brain Informatics (BI) is an emerging interdisciplinary field to study human information processing mechanism systematically from both macro and micro points of view by cooperatively using experimental, computational, cognitive neuroscience and advanced WI (Web Intelligence) centric information technology. It attempts to understand human intelligence in depth, towards a holistic view at a long-term, global vision to understand the principles and mechanisms of human information processing system, with respect to functions from perception to thinking, such as multi-perception, attention, memory, language, computation, heuristic search, reasoning, planning, decision-making, problem-solving, learning, discovery and creativity. (3)

Zhuge, Hai. Discovery of Knowledge Flow in Science. Communications of the ACM. 49/5, 2006. Insightful ways to implement the worldwide e-science knowledge grid so as to enhance its productivity and in turn improve our societies. One then wonders if such “autonomous” cerebral activity on a planetary scale might achieve its own salutary learning capacity.

The knowledge flow network implicit in the citation network consists of knowledge flows between nodes (scientists) that process knowledge, including reasoning, fusing, generalizing, inventing, and problem solving, by authors and co-authors. (103) Exploring the universe and human society are great challenges of 21st century science. This article explores the dynamic nature of knowledge, the power to promote and influence the development of human society, and the future interconnection environment. It describes an important approach to automatically discovering knowledge flow networks within scientific documents and activities. Such networks embody an autonomous knowledge grid, which supports individual and cooperative scientific research, helps investigate the evolution of knowledge and disciplines, and assists in planning for scientific research development. (107)

Zhuge, Hai. Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure. arXiv:1507.06500. A leading Chinese computer scientist, see bio below, continues his contributions to the salutary advancement of planetary and personal Internet design, capability, and access. Of interest are intimations of a New Paradigm of Science by way of these instant, collaborative worldwide endeavors, an e-science which is really an emergent human sapiensphere. See also his latest November 2016 book Multi-Dimensional Summarization in Cyber-Physical Society from Morgan-Kaufmann Publishers. Some years ago Professor Zhuge and I had a good exchanged emails which led to my review of his earlier work The Knowledge Grid (search) for a Chinese journal. See also The Complex Link at 1805.00434 for a later edition.

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing. (Abstract)

Hai Zhuge has appointments at Nanjing University of Posts and Telecommunications, Institute of Computing Technology in Chinese Academy of Sciences, and Aston University. Professor Zhuge is a recognized pioneer and leader Cyber-Physical Society research and Knowledge Grid research. His research in this area has received over 4,000 citations. He is a Distinguished Scientist of ACM, and a Fellow of British Computer Society, an Associate Editor of IEEE Intelligent Systems and Steering the International Conference on Semantics, Knowledge and Grids. He previously authored The Knowledge Grid -- Toward Cyber-Physical Society 2E, World Scientific Publishing Co (2012).

Zhuge, Hai. The Knowledge Grid. Singapore: World Scientific, 2004. The author is a professor of computer science at the Chinese Academy of Sciences and founder of the Chinese Knowledge Grid Research Group. This frontier volume explores the epistemologies, ontologies, semantics, systems principles, scale-free network properties, and so on of national and worldwide knowledge resources. By Knowledge Grid is meant an intelligent and sustainable interconnected network that allows and empowers people and their computers to access, publish, share and manage information resources. (An introductory article by Zhuge is The Future Interconnection Environment in Computer, April 2005.) A good example is Zhuge's work on creating a virtual model of the recent SARS epidemic, reported in the Planetary Physiology section. An extended review of this important work is posted in the Recent Writings section.

Intelligence, Grid, peer-to-peer and environment represent humanity's four aspirations for the future working and living environment. The intelligence reflects humanity's pursuit of recognizing themselves and the society. The Grid reflects humanity's pursuit of optimization and system. The peer-to-peer reflects humanity's pursuit of freedom and equality. The environment reflects humanity's pursuit of understanding of nature and its harmony. (27)

Zhuge, Hai and Xiaoqing Shi. Fighting Epidemics in the Information and Knowledge Age. Computer. October, 2003. A practical example of applying intelligent information processing to combat outbreaks such as the SARS virus.

Zhuge, Hai and Xiaoqing Shi. Toward the Eco-Grid: A Harmoniously Evolved Interconnection Environment. Communications of the ACM. 47/9, 2004. Further insights on recasting the Internet into a more organic, evolutionary and dynamically responsive noosphere.

An Eco-Grid is an open worldwide interconnection environment reflecting the characteristics of natural ecological environments. (80)

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