The only thing stronger than your imagination is your imagination connected to the billions of other imaginations all over the world, connected to smart machines that continue to get smarter, faster.
— Rita King (via inthenoosphere)

How should we choose among these dueling, high-profile…findings? Ioannidis suggests a simple approach: ignore them all…we consume thousands of nutrients that act together as a sort of network, and changing intake of just one of them is bound to cause ripples throughout the network that are far too complex…to detect…

'…The scientific enterprise is probably the most fantastic achievement in human history, but that doesn’t mean we have a right to overstate what we’re accomplishing.'

We could solve much of the wrongness problem…if the world simply stopped expecting scientists to be right…being wrong in science is fine, and even necessary—as long as scientists…report their mistake openly instead of disguising it as a success, and then move on to the next thing…But as long as careers remain contingent on producing a stream of research that’s dressed up to seem more right than it is, scientists will keep delivering exactly that.

'Science is a noble endeavor, but it’s also a low-yield endeavor,' …'I’m not sure that more than a very small percentage of medical research is ever likely to lead to major improvements in clinical outcomes and quality of life. We should be very comfortable with that fact.'

Lies, Damned Lies, and Medical Science
Rather, evolution experiences jumps in complexity (such as the emergence of a self-reflective universe, or noosphere). The complexification of human cultures, particularly language, facilitated a quickening of evolution in which cultural evolution occurs more rapidly than biological evolution
— Vernadsky (via inthenoosphere)

(via hdcmetable)

There are two types of people: type A and type B. Type A is much more frequent. Type A is the expert, the one who knows everything. They come to you with a plan with all the ideas and details worked out. They want to make sure that everybody participates in a consensus of what they are doing – these are the people I run away from as fast as I can. Type B however, you rarely see often. They have a vision, but are honest about the predicament and usually admit they have no clue how they will reach their end goal. This person has the strongest vision, and knows they will fail, but doesn’t mind failure.
— Sebastian Thrun, research professor of computer science at Stanford University, a Google fellow, a member of the National Academy of Engineering and the German Academy of Sciences (read full article here)

(Source: inthenoosphere)


From Crowdfunding To Open Access, Startups Are Experimenting With Academic Research

These days may well be the next golden age for universities, and startups are leading the way. For institutions that can feel much like their counterparts from a thousand years ago, universities have witnessed breathtaking change in just a handful of years.

Full Story: Techcrunch
A complex system is one whose component parts interact with sufficient intricacy that they cannot be predicted by standard linear equations; so many variables are at work in the system that its over-all behavior can only be understood as an emergent consequence of the holistic sum of the myriad behaviors embedded within. Reductionism does not work with complex systems, and it is now clear that a purely reductionist approach cannot be applied; …in living systems the whole is more than the sum of its parts. This is the result of… complexity which allows certain behaviors and characteristics to emerge unbidden.
— Levy (via inthenoosphere)
Complex adaptive systems operate in this transition zone between stable equilibrium points and complete randomness. Poised between solidity and precariousness, these regions are typically referred to as the edge of chaos. Neither stability nor chaos is capable of exhibiting the characteristics of complex systems—such behavior can only exist balanced at the edge of chaos. Strange attractors are products of nonlinearity and interactivity. In a sense, falling into attractor patterns produces a constraint on the system behavior; the system of interacting agents loses degrees of freedom in the variety of its activity pattern: “Once the components have entered into this mutual arrangement (attractor), they will tend to ‘stick’ to it, and no longer be able to undergo certain types of relative variation”.
— Heylighen (via inthenoosphere)
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