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The Power of Networks

The Power of Networks | wb | Scoop.it

Nowadays, any organization should employ network scientists/analysts who are able to map and analyse complex systems that are of importance to the organization (e.g. the organization itself, its activities, a country’s economic activities, transportation networks, research networks).Interconnectivity is beneficial but also brings in vulnerability: if you and I are connected we can share resources; meanwhile your problems can become mine and vice versa.The concept of “crystallized imagination” refers to things that are first in our head and then become reality. This concept can be turned into network applied research on economic complexity of a country’s economic activities and development prospects.


Via Ashish Umre
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Unsupervised Machine Learning, Most Promising Ingredient Of Big Data

Unsupervised Machine Learning, Most Promising Ingredient Of Big Data | wb | Scoop.it

Orange (France Telecom), one of the largest mobile operators in the world, issued a challenge “Data for Development” by releasing a dataset of their subscribers in Ivory Coast. The dataset contained 2.5 billion records, calls and text messages exchanged between 5 million anonymous users in Ivory Coast, Africa. Various researchers got access to this dataset and submitted their proposals on how this data can be used for development purposes in Ivory Coast. It would be an understatement to say these proposals and projects were mind-blowing. I have never seen so many different ways of looking at the same data to accomplish so many different things. Here’s a book [very large pdf, right-click to save instead of opening it online] that contains all the proposals. My personal favorite is AllAborad where IBM researchers used the cell-phone data to redraw optimal bus routes. The researchers have used several algorithms including supervised and unsupervised machine learning to analyze the dataset resulting in a variety of scenarios.


Via Ashish Umre
Bian Wu's insight:

a huge collections of data mining of the France telecom data

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Bill Aukett's curator insight, July 23, 2013 8:04 AM

Reminds that;

there can be many "right' answers to the same problem, 

you can spend time and money finding the "right"answer to tthe "wrong" problem, and

somestimes there are "issues to manage and not problems to solve" (Johnson , Polarity Management.)

 

Rescooped by Bian Wu from Amazing Science
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▶ Quantum Computers, AI, Genomics and the Development of a Super Intelligence

Suzanne Gildert's talk at Humanity+ @ Caltech ( http://www.humanityplus.org/conferences/ ) about "What do super-intelligences REALLY want?" and will they outsmart mankind during in a singularity event.

 

Here are the 10 D-wave technology presentation videos - lectures given by Dr. Suzanne Gildert in 2009

http://www.youtube.com/watch?v=gV2syNxDfe0
http://www.youtube.com/watch?v=fpvhRcIjGGU
http://www.youtube.com/watch?v=WKLGlInKzk8
http://www.youtube.com/watch?v=OTzLO2zQV2c
http://www.youtube.com/watch?v=rw1MmljlxWk
http://www.youtube.com/watch?v=tdFEOsAdBeE
http://www.youtube.com/watch?v=AxzietDpTrI
http://www.youtube.com/watch?v=b9uqO7q-v1g
http://www.youtube.com/watch?v=mpH8iOS8GwM
http://www.youtube.com/watch?v=sBNOAdfLX2I

or all together in a playlist:

http://www.youtube.com/watch?v=gV2syNxDfe0&feature=results_main&playnext=1&list=PLBE82A43D0A71BAB7

and here are her talks on quantum computing - is the end near for silicon chips?

http://www.youtube.com/watch?v=qyAndXYo9cA
http://www.youtube.com/watch?v=K3SvZ7KCZdI
http://www.youtube.com/watch?v=05FiZEjYB2A
http://www.youtube.com/watch?v=8essA5aUNgE
http://www.youtube.com/watch?v=PLk3vxi3_DY
http://www.youtube.com/watch?v=gEv4ccFutcI
http://www.youtube.com/watch?v=RXWWx57Iv-8

and her adiabatic QC talks plus her QC and AI talks in a playlist:

http://www.youtube.com/watch?v=wLY0lBwUHWw&feature=results_main&playnext=1&list=PLA4945FDEFBD5D5ED

My personal favorite is:

Where is machine intelligence going? What do superintelligences REALLY want?

http://www.youtube.com/watch?v=r8x_ohZJLx0

She is also the cofounder of carboncopies.org - and organization that works on connectome mapping of the brain and downloading memories.


Via Dr. Stefan Gruenwald
Bian Wu's insight:

artificial super intelligence. a lot of video reference

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Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity

Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity | wb | Scoop.it

We present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model’s connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments.


Via Ashish Umre
Bian Wu's insight:

close to my project

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Self-organization versus top-down planning in the evolution of a city

Interventions of central, top-down planning are serious limitations to the possibility of modelling the dynamics of cities. An example is the city of Paris (France), which during the 19th century experienced large modifications supervised by a central authority, the `Haussmann period'. In this article, we report an empirical analysis of more than 200 years (1789-2010) of the evolution of the street network of Paris. We show that the usual network measures display a smooth behavior and that the most important quantitative signatures of central planning is the spatial reorganization of centrality and the modification of the block shape distribution. Such effects can only be obtained by structural modifications at a large-scale level, with the creation of new roads not constrained by the existing geometry. The evolution of a city thus seems to result from the superimposition of continuous, local growth processes and punctual changes operating at large spatial scales.

 

Self-organization versus top-down planning in the evolution of a city
Marc Barthelemy, Patricia Bordin, Henri Berestycki, Maurizio Gribaudi

http://arxiv.org/abs/1307.2203


Via Complexity Digest
Bian Wu's insight:

now bring the self-organization and control to city planning

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We Finally Know Why You Can Sustain a Conversation in a Noisy Bar

We Finally Know Why You Can Sustain a Conversation in a Noisy Bar | wb | Scoop.it

Normally, human ears are incredibly good at focusing on sounds of specific frequencies and simultaneously filtering out the rest of the noise — your drinking buddy’s voice in a crowded bar, for example. This is why you can have conversations in places with a wild and crazy soundscape. If we paid attention to all the noises all the time, there would be no way to distinguish between your friend’s on-the-spot beer review and the clamor of vapid background conversations.

 

As we age, though, this ability to focus on particular frequencies wanes. Which is why, if you’re like me and enjoy hanging out with your parents in bars, you find yourself yelling more loudly as the years go on.

 


Via Ashish Umre
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