The Wisdom of Mold Despite its ability to solve an array of problems, the slime mold was designed by evolution to solve just one problem: how to build an optimal transport network (for its nutrients). So we decided to investigate how the slime mold, when presented with the task of connecting the major urban areas of the United States, would design a transport system. Would its design resemble that of the United States highway system, or would the slime mold propose a superior one? Here’s how our experiment worked. As we detail in a forthcoming article in the journal Complex Systems, we took a large dish in the shape of the United States and placed rolled oats (a food for the slime mold) in the locations of 20 major urban areas. Then we put the slime mold on the rolled oats representing the New York area. The slime mold propagated out from New York toward the other urban areas and eventually spanned them all with its network of protoplasmic tubes. We performed this experiment a number of times. What did the resulting network look like? It looked remarkably like the United States interstate highway system. We found that the slime mold approximated almost all interstates. Links from Dallas to Houston, from Chicago to Milwaukee and from New York to Boston were reproduced by the slime mold in almost all experiments. We also found that in three out of four experiments, the slime mold approximated the routes from the San Jose, Calif., area to Las Vegas; the chain of links connecting Denver to Albuquerque to the Phoenix area to the Los Angeles area; and the chain of links connecting Kansas City, Mo., to Oklahoma City to the Dallas area to the Houston area. It also approximated two chains — one connecting […]

“Let children play, because it’s never just play.” #education is how we manage the #attentioneconomy . via +Paul Harper Google in Education originally shared this post: How do humans learn? Born to Learn is the first animation in a fascinating series aimed to provide easy-access to the exciting new discoveries constantly being made about how humans learn. It is part of +YouTube Edu. #youtubeedu Born to Learn

The Zombie Within by Alva Noë Yes, athletes, musicians, drivers and chess players, when they are in the flow, can act fast without needing to make decisions about what to do. But this is not because they aren’t thinking. Nor is it because they are thinking really fast. It’s because they are thinking about what matters, such as the musical ideas or the traffic or the potential vulnerability of the King to attack. Mastery consists precisely in shifting attention from the mechanics of a task to, if you like, the task’s point. Nothing illustrates this better than the case of language itself. We learn to decline and conjugate so that we can talk. The learner of a second language needs to give painstaking attention to grammatical choices and rules. But conversation — thoughtful participation in the parry and thrust, the give and take — requires that we stop focusing on the grammar and start focusing on what we are doing. What is required is not that we become automata, or forget the grammar; what is required is that we become masters of it. More: http://www.npr.org/blogs/13.7/2012/05/18/153025680/the-zombie-within via Michelle Merritt

Depressed People Surf the Web Differently It turns out depressed persons spend a lot more time flipping around the Internet randomly, have less consistent usage times and use more file-sharing programs and (this one surprised me) sent out more e-mails. Researchers said the random Internet patterns (such as watching a video followed by an email to watching part of another video to reading part this article, etc.) could point toward trouble concentrating, a symptom of depression. Usage itself was erratic, too: some students would spend hours a day online then not touch the computer for two days. More info: http://www.medicaldaily.com/news/20120517/9915/depression-internet-usage.htm Via: http://dvice.com/archives/2012/05/depression-lead.php

Any sufficiently advanced civilization is indistinguishable from its garbage. +Bruce Sterling’s witty insight is elaborated brilliantly and hilariously by Slavoj Zizek in the clip below from the film Examined Life. This quote comes from IEEE’s article “Any Advanced Civilization is indistinguishable from nature” http://ieet.org/index.php/IEET/more/5795 Slavoj Zizek in Examined Life

Any sufficiently advanced civilization is indistinguishable from nature Despite our visions and desires for a more ecologically integrated kind of technology, the scientific paradigm, which underpins technological development, considers the world to be a machine. Ecologist Fern Wickson argues that humans are intertwined in a complex web of biological systems and cannot be included within a definition of nature where “an atom bomb becomes as ‘natural’ as an anthill” and wonders whether there is a better definition of nature [4]. Changing the definition of nature is not the solution to Wikson’s conundrum. The scientific method is actually responsible for this paradox. If the problem of human connectedness to the natural world is to be resolved, then science itself needs to change. Modern science relies on ‘natural laws’ that use mathematical proofs and the metaphor of machines to convey its universal truths. In the 1950s Robert Rosen observed that when physics is used to describe biology, a generalization occurs that distorts reality. Alan Turing noted in his essay on morphogenesis that mathematical abstraction couldn’t capture the richness of the natural world [6]. Life is a complex system that is governed by a variety of unique processes that machines simply do not possess. Life responds to its environment, constantly changes with time and is made up of functional components that enables life the ability to self-regulate [7]. Complexity challenges the epistemological basis on which modern science and industry are grounded. So what does complex science mean for our relationship with nature? Are we separate from or intrinsically connected to the natural world? In a complex system we are both. Our actions through technology are intrinsically governed by the physical and chemical constraints of the terrestrial environment, yet we also possess agency and a capacity to modify our surroundings. But if we are […]

The charts in the link are beautiful. http://io9.com/5911520/a-chart-that-reveals-how-science-fiction-futures-changed-over-time Jordan Peacock originally shared this post: A Chart that Reveals How Science Fiction Futures Changed Over Time io9 In the 1900s and the 1980s, there were huge spikes in near-future science fiction. What do these eras have in common? Both were times of rapid technological change. In the 1900s you begin to see the widespread use of telephones, cameras, automobiles (the Model T came out in 1908), motion pictures, and home electricity. In the 1980s, the personal computer transformed people’s lives. In general, the future got closer at the end of the twentieth century. You can see a gradual trend in this chart where after the 1940s, near-future SF grows in popularity. Again, this might reflect rapid technological change and the fact that SF entered mainstream popular culture. The future is getting farther away from us right now. One of the only far-future narratives of the 1990s was Futurama. Then suddenly, in the 2000s, we saw a spike in far-future stories, many of them about posthuman, postsingular futures. It’s possible that during periods of extreme uncertainty about the future, as the 00s were in the wake of massive economic upheavals and 9/11, creators and audiences turn their eyes to the far future as a balm. A Chart that Reveals How Science Fiction Futures Changed Over Time

Jon Lawhead originally shared this post: This is Yaneer Bar-Yam’s “A Mathematical Theory of Strong Emergence Using Multi-Scale Variety.” It, along with the other paper of his I just posted, is going to turn out to be one of the most significant papers of the 21st century. I would bet money on it. Integrating the insight in these two papers into contemporary philosophy of science (and expanding on them) is one of the central pillars of my overall professional project. #complexitytheory is the next big scientific paradigm shift. All the pieces are out there now (these two papers are two of them); we just need to put them all together into a unified, coherent narrative. The first person/people to do that will go down in history as being the Darwin of the 21st century. I’ll race you. #science #emergence #complexsystems #selforganization http://www.necsi.edu/research/multiscale/MultiscaleEmergence.pdf

+Christine Paluch Kevin Clift originally shared this post: Subway Maps Converge Mathematically There are mathematical similarities between subway/underground systems that have been allowed to grow in response to urban demand, even though they may not have been planned to be similar. Understand those principles, and one might “make urbanism a quantitative science, and understand with data and numbers the construction of a city,” said statistical physicist Marc Barthelemy of France’s National Center for Scientific Research. More here: http://www.wired.com/wiredscience/2012/05/subway-convergence/ Paper: http://rsif.royalsocietypublishing.org/content/early/2012/05/15/rsif.2012.0259 Sample of subway network structures from (clockwise, top left) Shanghai, Madrid, Moscow, Tokyo, Seoul and Barcelona. Image: Roth et al./JRSI

#complexity scientists are already watering at the mouth for #exascale computing. This is a fabulous demonstration of what they can already do at petascale levels. From http://news.stanford.edu/news/2012/may/engineering-hypersonic-flight-051512.html One reason computational uncertainty quantification is a relatively new science is that, until recently, the necessary computer resources simply didn’t exist. “Some of our latest calculations run on 163,000 processors simultaneously,” Moin said. “I think they’re some of the largest calculations ever undertaken.” Thanks to its close relationship with the Department of Energy, however, the Stanford PSAAP team enjoys access to the massive computer facilities at the Lawrence Livermore, Los Alamos and Sandia national laboratories, where their largest and most complex simulations can be run. It takes specialized knowledge to get computers of this scale to perform effectively, however. “And that’s not something scientists and engineers should be worrying about,” said Alonso, which is why the collaboration between departments is critical. “Mechanical engineers and those of us in aeronautics and astronautics understand the flow and combustion physics of scramjet engines and the predictive tools. We need the computer scientists to help us figure out how to run these tests on these large computers,” he said. That need will only increase over the next decade as supercomputers move toward the exascale – computers with a million or more processors able to execute a quintillion calculations in a single second. Modeling the Complexities of Hypersonic Flight via +Amy Shira Teitel!