Showing posts with label event horizon. Show all posts
Showing posts with label event horizon. Show all posts

Tuesday, May 24, 2011

Rebuilding Iberian Motorways with Slime Mould

Wet machines and Soft Computers planning road routes organically. 

Place your 'problem' in bag and shake to get the answer!






Although done on a simple flat map/surface there is no reason why this couldn't be a 3d model with variable temperatures/variables throughout. The modelling of landscapes can be more accurate organically in order to find target map paths that are efficient from a biologic standpoint.

These types of navigational problems* were among some of the first tackled by 'hard' machines (computers like you are reading this with) when they were first developed and it's nice to see the initially parallel development of bio computing.


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* Travelling Salesman problem : What is the shortest route visiting each city exactly once and then returns to the starting city? See more classic computing problems here 









Thursday, April 10, 2008

The Prediction Model

I've become increasingly interested in the overlap of biology and computing over the past few years. It began with the realisation that the web and stock market are really biologic in nature with their fault tolerance, nodal shape, replication of information and distributed locus of control and was further prompted by work I undertook on AI systems for Advertising and Social Computing solutions.

I’m enjoying this overlap developing into a moderate obsession and I am trying to steer my thinking on all things computing into a more ‘biologic fashion’. I’ve always been a strong believer that people involved in one discipline can offer fresh insights on other sciences and that a good set of ‘first principals’ can work well cross domain. This cross pollination was the grease that helped the machine of the Industrial Revolution into being and obliquely it’s also the reason I give for sporting sideburns like some Manchester factory owner.

This post is inspired by Jeff Hawkins who is doing work into models of the brain and attempting to derive an overarching theory of the brain which is something that, despite the reams of data we have on the brain, we are as yet unable to articulate. His talk was on the use of a Prediction Model as the primary approach to developing a theory of the brain and he got my mind racing.

After graduating from Cornell in June 1979 he read a special issue of Scientific American on the brain. In it Francis Crick lamented the lack of a grand theory explaining how the brain functions.[3] Initially, he attempted to start a new department on the subject at his employer Intel, but was refused. He also unsuccessfully attempted to join the MIT AI Lab. He eventually decided he would try to find success in the computer industry and then try to use it to support his serious work on brains, as described in his book On Intelligence

Jeff thinks that the reason we still haven’t managed to define intelligence well is that we don’t have this overarching theory of the brain or more accurately – intelligence. Jeff postulates that the brain isn't like a powerful computer processor and that instead it’s more like a memory system that records everything we experience and helps us predict, intelligently, what will happen next.

Things like these stop me sleeping at night and last Sunday I leaned over to my girlfriend at 2am and whispered to her “I have to write some stuff”.

I slipped out of bed and knocked up the notes below. They are presented here un-edited and what you see is the first pass brain dump of some of my thoughts and concepts surrounding a Prediction Model (It's probably best to click on one and open up the set in Flickr and view from there).

If you are involved in this area at all I would love to hear from you as I intend to delve deeper. Physics has alot to add to this area with work in quantum theory and calculations surrounding boundaries of event horizons for black holes all being of relevance to the model of the brain and prediction.






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