Complex Insight - Understanding our world
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Complex Insight  - Understanding our world
A few things the Symbol Research team are reading.  Complex Insight is curated by Phillip Trotter (www.linkedin.com/in/phillip-trotter) from Symbol Research
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Fast and slow thinking -- of networks: The complementary 'elite' and 'wisdom of crowds' of amino acid, neuronal and social networks

Complex systems may have billion components making consensus formation slow and difficult. Recently several overlapping stories emerged from various disciplines, including protein structures, neuroscience and social networks, showing that fast responses to known stimuli involve a network core of few, strongly connected nodes. In unexpected situations the core may fail to provide a coherent response, thus the stimulus propagates to the periphery of the network. Here the final response is determined by a large number of weakly connected nodes mobilizing the collective memory and opinion, i.e. the slow democracy exercising the 'wisdom of crowds'. This mechanism resembles to Kahneman's "Thinking, Fast and Slow" discriminating fast, pattern-based and slow, contemplative decision making. The generality of the response also shows that democracy is neither only a moral stance nor only a decision making technique, but a very efficient general learning strategy developed by complex systems during evolution. The duality of fast core and slow majority may increase our understanding of metabolic, signaling, ecosystem, swarming or market processes, as well as may help to construct novel methods to explore unusual network responses, deep-learning neural network structures and core-periphery targeting drug design strategies.

 

Fast and slow thinking -- of networks: The complementary 'elite' and 'wisdom of crowds' of amino acid, neuronal and social networks
Peter Csermely

http://arxiv.org/abs/1511.01238 ;


Via Complexity Digest
Complexity Digest's curator insight, November 18, 2015 6:13 PM

See Also: http://networkdecisions.linkgroup.hu 

António F Fonseca's curator insight, November 23, 2015 3:30 AM

Interesting  paper about fast cores and slow periphery,  conflict in the elite vs democratic consensus.

Marcelo Errera's curator insight, November 24, 2015 11:32 AM

Yes, there must be few fasts and many slows.  It's been predicted by CL in many instances.

 

http://www.researchgate.net/publication/273527384_Constructal_Law_Optimization_as_Design_Evolution

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How bio-inspired deep learning keeps winning competitions | KurzweilAI

How bio-inspired deep learning keeps winning competitions | KurzweilAI | Complex Insight  - Understanding our world | Scoop.it

Good inverview with Dr. Jürgen Schmidhuber, Director of the Swiss Artificial Intelligence Lab, IDSIA. His research team’s artificial neural networks (NNs) have won many international awards, and recently were the first to achieve human-competitive performance on various benchmark data sets. IDSIA are probably the current world leaders in ANN research and the quality of what they do is rather insipiring. worth reading.

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What Neuroscience Really Teaches Us, and What It Doesn't

What Neuroscience Really Teaches Us, and What It Doesn't | Complex Insight  - Understanding our world | Scoop.it

Great article in the New Yorker explaining why claims that a certain part of the brain is responsible for a given function while making good headlines - often is not as simple as it seems. The smallest element of a brain image that an fMRI can pick out is something called a voxel. But voxels are much larger than neurons, and, in the long run, the best way to understand the brain is probably not by asking which particular voxels are most active in a given process. It will instead come from asking how the many neurons work together within those voxels. And for that, fMRI may turn not out not to be the best technique, despite its current convenience. It may ultimately serve instead as the magnifying glass that leads us to the microscope we really need. If most of the action in the brain lies at the level of neurons rather than voxels or brain regions (which themselves often contain hundreds or thousands of voxels), we may need new methods, like optogenetics or automated, robotically guided tools for studying individual neurons; Click on the title or image to learn more.

 

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Inside Paul Allen's Quest To Reverse Engineer The Brain

Inside Paul Allen's Quest To Reverse Engineer The Brain | Complex Insight  - Understanding our world | Scoop.it

thanks to Jed for the heads up on this. Great article from Forbes on Microsoft cofounder Paul Allen's  Allen Institute for Brain Science research institute who are pursuing a big science approach to understanding the workings of the human brain. Well worth reading. Click on the headline or image to learn more.

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Scientists discover workings of brain's 'GPS System' - Indian Express

Scientists discover workings of brain's 'GPS System' - Indian Express | Complex Insight  - Understanding our world | Scoop.it
Scientists discover workings of brain's 'GPS System' - Scientists have discovered how the brain's internal system works to determine the body's location as it moves through its sur
Phillip Trotter's insight:

The study from researchers at Princeton University found that certain position-tracking neurons - called grid cells - ramp their activity up and down by working together in a collective way to determine location. Grid cells are neurons that become electrically active, or "fire," as animals travel in an environment. First discovered in the mid-2000s, each cell fires when the body moves to specific locations, for example in a room. The neuronal locations are arranged in a hexagonal pattern like spaces on a Chinese checker board and together the grid cells form a representation of space according to David Tank, Princeton's Henry L Hillman Professor in Molecular Biology and leader of the study. Click on the image or title to learn more.

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Jeff Hawkins Develops a Brainy Big Data Company

Jeff Hawkins Develops a Brainy Big Data Company | Complex Insight  - Understanding our world | Scoop.it

Interesting article in The New York Times on Jeff Hawkins (of Palm computer fame) new company Numenta. Their Grok product uses a complex artificial neuron model to build predictive analytics from sensed data. Worth reading. Click on the image or the title to learn more. 

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The Brain in the Machine: I.B.M's Compass

The Brain in the Machine: I.B.M's Compass | Complex Insight  - Understanding our world | Scoop.it

I.B.M. has just announced the world’s grandest simulation of a brain, all running on a collection of ninety-six of the world’s fastest computers. Are full-scale simulations of human brains imminent, as some media accounts seem to suggest? Good article in the New Yorker, on the Compass project to simualte the brain of a Macaque monkey using the neuromorphic engineering approach pioneered by Carver Mead. Worth reading. Click on the the title or image to learn more.

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Bees Solve Complex Problems Faster Than Current Supercomputers

Bees Solve Complex Problems Faster Than Current Supercomputers | Complex Insight  - Understanding our world | Scoop.it
In a landmark 2010 study, researchers found that bumblebees were able to figure out the most efficient routes among several computer-controlled "flowers," quickly solving a complex problem that even stumps supercomputers. We already know bees are pretty good at facial recognition, and researchers have shown they can also be effective air-quality monitors.

 

Bumblebees can solve the classic "traveling salesman" problem, which keeps supercomputers busy for days. They learn to fly the shortest possible route between flowers even if they find the flowers in a different order, according to the British study.

 

The traveling salesman problem is a problem in computer science; it involves finding the shortest possible route between cities, visiting each city only once. Bees are the first animals to figure this out, according to Queen Mary University of London researchers.


Via Dr. Stefan Gruenwald
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