Member 2604
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Contributor to projects:
The Total Library
Yokohama, JP
Immortal since Apr 23, 2010
Uplinks: 0, Generation 4

Emergent day to you. 2010-04-22 is my knowmad birthday. Think I understood the word. More to emerge.
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    CoCreatr’s projects
    The human species is rapidly and indisputably moving towards the technological singularity. The cadence of the flow of information and innovation in...

    The Total Library
    Text that redefines...
    Now playing SpaceCollective
    Where forward thinking terrestrials share ideas and information about the state of the species, their planet and the universe, living the lives of science fiction. Introduction
    Featuring Powers of Ten by Charles and Ray Eames, based on an idea by Kees Boeke.

    OVERVIEW from Planetary Collective

    On the 40th anniversary of the famous ‘Blue Marble’ photograph taken of Earth from space, Planetary Collective presents a short film documenting astronauts’ life-changing stories of seeing the Earth from the outside – a perspective-altering experience often described as the Overview Effect.

    Synapsing with an interview

    Jamais Cascio - The Future and You! Security, Privacy, AI, Geoengineering

    Jamais Cascio discusses the Participatory Panopticon, Privacy & Secrecy, the ramifications of Disconnecting from the Chorus, what it means to be a Futurist, the Arc of Human Evolution, Artificial Intelligence, the Need for Meaning, Building Agents to Listen to Us, /, Geoengineering and the Viridian Green movement.
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    A meme
    to meditate about
    what it means
    to be in a tribe,
    to lead, to follow, or
    to get out of the way.

    Embrace the we among us.

    Let them thrive.

    By choice, you are part of the we.

    And if not you,

    someone is.

    Making you part of us.

    Click image to download Tribes Q&A, free ebook (pdf, 1.4MB)


    Wed, Jan 18, 2012  Permanent link
    Categories: collective intelligence, polytopia, knowmad, tribe
    Sent to project: Polytopia
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    Jeff Jonas wrote in General Purpose Sensemaking Systems and Information Colocation

    ... With information trapped in the tailored database schemas of systems of record, operational data stores, data warehouses and data marts, it is no wonder organizations continue to struggle to make sense of it all – despite decades of effort and innovation.

    Performing some kind of federated search over all these disparate data sets just has not ever delivered. In fact, federated search bites when it comes to sensemaking because the diverse data structures are incapable of supporting a sensemaking function.

    If you want to be smart, you will want to jam the available, diverse, observational space into the same data structure and in as close to the same physical space as possible.

    Data is data.

    When reference data, transactional data, and even user queries are colocated in the same data structures and is the same indexes as the extracted features from text, video, biometrics, and so on … something very exciting happens: data naturally finds data and context can accumulate.


    Long story short, when this general sensemaking system came on-line it started finding marketing hosts comping their roommates and lots of other unanticipated novel discovery. So much novel discovery, it earned the name Non-Obvious Relationship Awareness or NORA, we got two rounds of funding, IBM bought my company to get its hands on the technology, and the rest is history.

    Simply said, you have to have a brain (multi-purpose, general structure) to think (sense make). Then with a brain, the smartest you are going to be is a function of what observations you have properly contextualized into that meat space between your ears.

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    The science of complex systems is transforming science and its role in society. Building on the traditional focus on the parts of systems, the new approach integrates the networks of relationships within and between systems. These relationships are responsible for the collective "emergent" behaviors we see in all physical, biological, socio-economic and technological systems.

    Complex systems research can answer questions previously considered outside of the realm of scientific inquiry. This includes using science to understand human behavior, social interactions, and the consequences of policies and decisions of our society.


    • overview
      multiscale method
      ethnic violence
      evolution & ecology
      systems biology
      military conflict

    Evolution and Ecology

    NECSI’s research into evolution clarifies basic issues in evolutionary dynamics such as how altruism arises, the origin and characterization of biodiversity, as well as the interplay of evolution with ecology. Specific work addresses:

    • Patterns in Space and the Dynamics of Evolution
      The gene-centered view as a dynamic version of the mean field approximation
      Biodiversity and spatial symmetry breaking
      Genealogical trees and biodiversity
      Estimating the diversity of a population from a sample
      Evidence for why reproductive fitness isn’t necessarily predictive of long term survival
      Environment modification and inheritance
      Origins of altruism, including altruism by social signaling
      Sewall Wright's shifting balance theory
      Celllular automata models of evolutionary self-replication

    Preserved on 2011-11-02 from
    New England Complex Systems Institute (NECSI)
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    Despite its often contended (and oft-contentious) meanings, legal academics and educators still resort to the now-entrenched phrase,“think like a lawyer,” to describe the goal of law schools in educating their students. But even a brief deconstruction of the phrase brings its varied interpretations to light: What does it mean to “think like a lawyer”? It might easily imply an existing difference from thinking like a doctor, a banker, or a representative from another profession. But within the law, does “think like a lawyer” exclude thinking like a judge or a legislator (both roles comprising those who might have been lawyers in another life)? And which lawyer for that matter? Erwin Chemerinsky? Oliver Wendell Holmes? Perry Mason? An average, reasonable lawyer? A “bad” lawyer? To attempt to tease out the “definable” components of the phrase reveals the phrase’s imprecision, and the difficulties in using “think like a lawyer,” as a proscribed law teaching goal.

    Borrowing from the notion established by notable law professors, Michael Hunter Schwartz, Sophie Sparrow, and Gerald Hess, that the goal of teaching law students should be to allow students to accomplish effective legal problem-solving rather than thinking like a lawyer, this Article focuses on the teaching of one particular skill needed for such problem-solving: how legal thinkers methodically and effectively approach reading, comprehending, and critiquing the law. Language comprises the nuts and bolts of the law, but law school curricula generally do not focus on sharpening the elevated levels of perception needed for legal thinkers to internally process case holdings, blackletter rules, and statutes for whatever tasks await them. In fact, the traditional case method of teaching law students to “think like a lawyer” often only briefly and abstractly addresses the components of legal reading and then expects students to master the skills out on their own, which poses increasing problems in light of the noted decline of literacy and comprehension skills in the recent adult population in the U.S.

    This Article addresses an approach to teaching legal literacy skills through deconstruction from both within the law and as an import from post-modernist thought. By doing so, this Article explores how teaching one method of rule reading and comprehension—termed “rule deconstruction”—to first-year law students introduces them to both formalist and anti-formalist techniques to approaching the language of the law and equips them with the heightened sensitivity that legal thinkers must embrace for dealing with legal reading. First the Article will first present a method of teaching “rule deconstruction” in its prima facie meaning to introduce a formalist perspective to breaking down complex legal rules and legislative materials in class that can link rule comprehension to student outlining skills and exam performance. Then the Article will take “deconstruction” in its post-structuralist incarnation and harness its postmodern tendencies into an anti-formalist method for dealing with the language of rules that can take student comprehension of rules into a more critical and theoretical realm. All of this is done with the goal of equipping the law student with both a hands-on and theoretical engagement with rules that challenges them to be both better legal thinkers and problem-solvers as well.

    From the SelectedWorks of Jeremiah A Ho, September 2010

    Full text, 98 pages, download immediately via or view in context.

    See also SelectedWorks
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    Monica Anderson explains.

    Reductionism is an amazingly powerful strategy for leveraging the work of scientists and for disseminating the results in the form of re-usable models of structure and causality. But for some of the "remaining hard problem domains" such as Life (biology, psychology, ecology, etc), the World (world modeling, economies, sociology), Intelligence (understanding the brain, intelligence, and creating Artificial General Intelligences - AGI) and the problem of determining the semantics of language (e.g. text) Reductionism has failed. I claim that reductionist models cannot be created in these domains (which have been named "Bizarre Domains") and that we must use Model Free (Holistic) Methods for these domains. This has important implications for AGI research strategies.

    "AI is the last holdout of pure reductionism, if you will."

    AGI: Artificial General Intelligence. In later lectures she uses AN: Artificial iNtuition.

    Slow down and enjoy the presentation. 31:22
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    A New Direction In AI Research

    Monica Anderson
    proposes adding a new target to ongoing AI research efforts: We need to focus more of our attention on Understanding as opposed to Reasoning. Understanding requires using Model Free Methods. As a bonus towards the end, Ms. Anderson also speculates about the so-called AI singularity and discusses whether SkyNet like scenarios, where computers take over the world, are plausible.

    Mechanical manipulation of formulas, even in the most strictly logical contexts require intuition-based guidance in order to progress towards a goal, such as simplification.
    Intuition is an invisible but non-mystical process....

    Intuition is fallible, that is why it is not a good basis to use in science...

    Intuition is the art of guessing wisely, based on a lifetime of gathered experience, stored as patterns...

    Monica Anderson

    Does it make sense to you?

    Why does the mind enjoy #simplicity? Because once you get it (conceptual understanding), things do get simple.

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