The Emergent Brain

Connecting dots for a global brain.

Archive for the ‘Collective Organisms’ Category

Johnson on the emergence of ideas

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Ideas are networks and develop in (liquid) networks. They emerge in open innovative systems.

Via TED Talks:

“People often credit their ideas to individual “Eureka!” moments. But Steven Johnson shows how history tells a different story. His fascinating tour takes us from the “liquid networks” of London’s coffee houses to Charles Darwin’s long, slow hunch to today’s high-velocity web.”

Watch the video here or below:

Mentioned in the talk is Matt Ridley’s talk earlier on the same topic.

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Written by emergentbrain

23/09/2010 at 00:47

Ridley on the emergence of ideas

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The exchange of ideas creates  highly specialized system based on comparative advantage, community and collaboration. And highly specialized systems can only sustain via a collective brain – where individuals can create things they don’t understand. They are just the nodes, the neurons in this collective brain. And we are surely accelerating the rate of innovation – an innovation beyond our personal capabilities.

Via TED Talks:

“At TEDGlobal 2010, author Matt Ridley shows how, throughout history, the engine of human progress has been the meeting and mating of ideas to make new ideas. It’s not important how clever individuals are, he says; what really matters is how smart the collective brain is.”

Watch the video here or below:

Written by emergentbrain

23/09/2010 at 00:41

Swarm intelligence for preferred outcomes 1

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If some human social system movements can be 93% predictable, animal social systems and their movement might help in even better and faster predicting certain real-world patterns and outcomes. A whole new branch of research has emerged around decoding and using swarm systems and intelligence in the last two decades. The Economist has a nice story giving an overview on this development focusing on insect, bird and robot behavior.

This basic analysis helps in understanding special decision making processes that are of short- to medium-term focus and can thus be determined by individuals themselves. Goals include route optimization, choice maximization and escape and emergency planning, in short: Movement patterns. Models based on swarm intelligence mentioned in the Economist article include such programs as Ant Colony Optimization and Particle Swarm Optimization that focus on self-reinforcing behavior and choice (some further models can be found in the Wikipedia). Modeling these kinds of behavior into algorithms seems quite easy, as they follow few rules. An older TED Talk by Steven Strogatz highlights the ease and power of synchronization in swarms based on only four rules – follow your nearest neighbor, line up, be attracted and move out in case of danger:

“Mathematician Steven Strogatz shows how flocks of creatures (like birds, fireflies and fish) manage to synchronize and act as a unit — when no one’s giving orders. The powerful tendency extends into the realm of objects, too.”

Watch the video here or below:

Thus, already in the general day-to-day behavior we can see a predictable pattern emerging based on few rules. Part 2 on swarm intelligence will cover higher, long-term cooperative systems of social organization that include generations and personal life roles.

Written by emergentbrain

22/09/2010 at 10:52

Christakis on predictions through social networks

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On the “collective existence of emotions” and other collective states of mind.

Via TED Talks:

“After mapping humans’ intricate social networks, Nicholas Christakis and colleague James Fowler began investigating how this information could better our lives. Now, he reveals his hot-off-the-press findings: These networks can be used to detect epidemics earlier than ever, from the spread of innovative ideas to risky behaviors to viruses (like H1N1).”

You might also want to check out his earlier TED appearance.

Watch the video here or below:

Written by emergentbrain

20/09/2010 at 14:40