Open source for reporting history - For historical method open source could mean, like it does for the programming world, a level down from open access, not only a convenient and egalitarian catalogue of freeware or finished articles but the actual revealing of the source-codes used...
Steve Shirley went on to become the world’s first freelance programmer and founded the software company F.I. Group in 1962, one of the UK’s earliest startups. It was a revolutionary company, writing software only — an outrageous proposition at the time. It was managed and operated by highly skilled female engineers.
When F.I. was eventually floated on the London Stock Exchange in 1996, it earned hundred of millions of pounds.
Darkly Digital Over the past few years as we’ve watched the digital revolution help bring about political and social revolutions around the world, it has seemed inevitable that the Internet would set people free...
Lecture about the rise of digital fabrication and parametric design, looking at their implications for creative practices. Specifically, Open Source design (Makerbot and Thingiverse), generative systems and data sculpture.
I have a brain cancer. I converted my digital medical records into open, accessible formats, turning them into a very personal form of Open Data. Artists, scientists, doctors, designers, hackers are all invited to send me their cure.
the rise of human technology, watch the TEDxtalk on the site
It is futile to ask whether people are naturally cooperative or selfish. They can be either, depending on the circumstances. Dr. Helbing cites "tragedies of the commons" where open access to a common-pool resource such as a fishery tends to result in overfishing that harms everybody—a sort of extended real-world version of the prisoner's dilemma.
In an increasingly interconnected world, scientists are seeking safeguards against catastrophic cascades of failure like stock market crashes and widespread blackouts.
Three years ago, Stanley and his colleagues discovered the mathematics behind what he calls “the extreme fragility of interdependency.” In a system of interconnected networks like the economy, city infrastructure or the human body, their model indicates that a small outage in one network can cascade through the entire system, touching off a sudden, catastrophic failure.
Onstage at TED2013, Sugata Mitra makes his bold TED Prize wish: Help me design the School in the Cloud, a learning lab in India, where children can explore and learn from each other -- using resources and mentoring from the cloud.
a brilliant thought in the future of education, Sugata Mitra won TED prize this month
As systems grow increasingly complex, it becomes impossible to identify or test for every possible cause of failure, writes Guest Columnist Irving Wladawsky-Berger.
There is a continuing struggle between complexity and robustness in both evolution and human design. A kind of survival imperative, whether in biology or engineering, requires that simple, fragile systems become more robust. But the mechanisms to increase robustness will in turn make the system considerably more complex. Furthermore, that additional complexity brings its own unanticipated failure modes, which are corrected over time with additional robust mechanisms, which then further add to the complexity of the system, and so on. This balancing act between complexity and robustness is never done.
The classic approaches to safety assumed that accidents are caused by component failures or by human error. Introducing fault tolerance techniques and planning for their failure will help prevent accidents, thus making components very reliable. Similarly rewarding safe human behavior and punishing unsafe behavior will eliminate or significantly reduce accidents.
These assumptions no longer apply, especially for complex, sociotechnical systems–that is, systems that combine powerful digital technologies with the people and organizations that use and support them.
LigWe assume design will make things 'better', but what do we mean by better? Longer-lasting? Cheaper? Sustainable? Hi-tech? Whose 'better' ultimate shapes our common future? Now synthetic biology is attempting to transform biology -- and life with it -- into a design and engineering discipline, finding ways to ask these questions is as important as ever. Daisy will talk about her work within synthetic biology, asking: can we use design to shape our future, rather than perpetuate the present?.
Support is growing for a decades-old physics idea suggesting that localized episodes of disordered brain activity help keep the overall system in healthy balance.
Bak’s hypothesis implies that most of the time, the brain teeters on the edge of a phase transition, hovering between order and disorder.
The brain is an incredibly complex machine. Each of its tens of billions of neurons is connected to thousands of others, and their interactions give rise to the emergent process we call “thinking.” According to Bak, the electrical activity of brain cells shift back and forth between calm periods and avalanches — just like the grains of sand in his sand pile — so that the brain is always balanced precariously right at that the critical point.
2014 : WHAT SCIENTIFIC IDEA IS READY FOR RETIREMENT?
Geoffrey WestDistinguished Professor and Past President, Santa Fe InstituteThe Theory of Everything
Everything? Well, wait a minute. Questioning A Theory of Everything may be beating a dead horse since I’m certainly not the first to be bothered by its implicit hyperbole but let’s face it, referring to one’s field of study as The Theory of Everything smacks of arrogance and naivité. Although it’s only been around for a relatively short period and may already be dying a natural death, the phrase, though certainly not the endeavour, should be retired from serious scientific literature and discourse.
Many thinkers have argued that studying philosophy is learning how to die. If that’s true, then we have entered humanity’s most philosophical age.
"...The biggest problems the Anthropocene poses are precisely those that have always been at the root of humanistic and philosophical questioning: “What does it mean to be human?” and “What does it mean to live?” In the epoch of the Anthropocene, the question of individual mortality — “What does my life mean in the face of death?” — is universalized and framed in scales that boggle the imagination. What does human existence mean against 100,000 years of climate change? What does one life mean in the face of species death or the collapse of global civilization? How do we make meaningful choices in the shadow of our inevitable end? These questions have no logical or empirical answers. They are philosophical problems par excellence. Many thinkers, including Cicero, Montaigne, Karl Jaspers, and The Stone’s own Simon Critchley, have argued that studying philosophy is learning how to die. If that’s true, then we have entered humanity’s most philosophical age — for this is precisely the problem of the Anthropocene. The rub is that now we have to learn how to die not as individuals, but as a civilization..."
Scientists have derived a series of mathematical formulas that describe how cities' properties vary in relation to their population size, and then posits a novel unified, quantitative framework for understanding how cities function and grow.
"It's an entirely new kind of complex system that we humans have created," he says. "We have intuitively invented the best way to create vast social networks embedded in space and time, and keep them growing and evolving without having to stop. When that is possible, a social species can sustain ways of being incredibly inventive and productive."
A model describing the brain as a system close to a phase transition can capture the global dynamics of brain activity observed in fMRI experiments.
Critical systems can be defined as systems that are close to a critical point, generally identified as the boundary of an order-disorder phase transition. Many complex systems far from equilibrium and composed of a large number of interacting elements have been successfully modeled as critical: notable examples range from gene-interaction networks to financial markets. At criticality, these systems can avoid being trapped in one of two extreme cases: a disordered state (when interactions are too weak and the system is dominated by noise) or a globally ordered state in which all elements are locked (when interactions are too strong and the system is completely static). Neither state supports the dualism essential for a complex system like the brain to function: it must maintain some order to ensure coherent functioning (i.e., generate a reproducible behavior in response to a certain stimulus) while allowing for a certain degree of disorder to enable flexibility (i.e., adapt to varying external conditions). Such dualism is instead possible at criticality.
Dynamical systems that maximize their future possibilities behave in surprisingly “intelligent” ways.
The second law of thermodynamics—the one that says entropy can only increase—dictates that a complex system always evolves toward greater disorderliness in the way internal components arrange themselves. In Physical Review Letters, two researchers explore a mathematical extension of this principle that focuses not on the arrangements that the system can reach now, but on those that will become accessible in the future. They argue that simple mechanical systems that are postulated to follow this rule show features of “intelligence,” hinting at a connection between this most-human attribute and fundamental physical laws.
Bottom-up processes in areas such as transportation can create cities that actually work for residents.
The autocatalytic city contains an intelligence, a kind of ingenuity that can never be captured by a top-down system of control. So it is almost poetic that the complexity of the city finds an analogue and an ally in the nonhierarchical complexity of the Internet. In much the same way that the autocatalytic city makes maximum use of physical materials and space, it is also co-opting technology into its fabric.
If you've ever wondered whether mammalian evolution has a speed limit, here's a number for you: 24 million generations.
That’s how many generations a new study estimates it would take to go from mouse- to elephant-sized while operating on land at the maximum velocity of change. The figure underscores just how special a trait sheer bigness can be.
“Big animals represent the accumulation of evolutionary change, and change takes time,”