Iterating Towards Bethlehem(rifters.com)

86 pointsby bane15 yıl önce7 comments

http://www.rifters.com/real/2009/01/iterating-towards-bethlehem.html

3 comments

calydon15 yıl önce

Peter Watts became the living master of hard scifi, (imo), with "Blindsight". In that book he first described (in terms that someone like me could understand) a cognition that rivals and surpasses human intelligence, by an alien creature that is 'unconscious'. It's so counter-intuitive to human thought (and arrogance) that something can be autonomous (unaware of its own actions) yet still work with purpose and according to a strategy that benefits its interests. Because the systems that are needed to maintain awareness are not present, this is in fact a faster and less error-prone method of thinking. He also does a neat trick where the aliens can communicate with us, despite having no understanding of what they are saying. I would have to re-read that part of the book to offer an explanation, but it involves grammar and information theory.

I would like to know, is this study of crypto-intelligence a recognized field and is Peter Watts at the forefront of this study, or is he getting his ideas from a disconnected body of experts?

barry-cotter15 yıl önce

Ctrl + F "Sentience/Intelligence" on the below link and you will get to the absolutely most relevant bits to your question. Crypto-intelligence isn't big enough to be a field but cognitive science is, and it covers all the interesting bits of neuroscience, psychology and philosophy.

http://www.rifters.com/real/Blindsight.htm#Notes

bane15 yıl önce

Now I'm intrigued. Thanks for giving me a book that's just gone to the top of my reading pile!

This idea of a brain, able to emulate a more powerful brain makes a kind of intuitive sense, or the number of neurons required for complex thinking is far lower than our understanding allows.

jamesbritt15 yıl önce

He also does a neat trick where the aliens can communicate with us, despite having no understanding of what they are saying.

"The Chinese Room Argument"

http://plato.stanford.edu/entries/chinese-room/

JoshTriplett15 yıl önce

The article seems to use "turing machine" or "emulator" in a more figurative sense, not to mean that the spider's neural network literally simulates simple rules that emulate a brain. The analogy to timeslicing makes more sense: the state of a computation can take less neural-network space than the ongoing computation, so switch between them and remember the variable values.

Also, the broader speculation in this article reminds me of https://www.xkcd.com/505/

huhtenberg15 yıl önce

A thought.

Perhaps her neurons are different, i.e. she could rewire some part of her brain as needed - forgetting past experience to free up the capacity for the new one - and this is why it takes hours of setup (observation) and this is why she can do it over and over again within the confines of 600K neurons.

bl15 yıl önce

Synapse "rewiring" is not typically how we think memories are formed in adult animals. Mostly it is done by modulating the strengths of the existing connections (this process involves signaling cascades and protein expression, so it does take some time). So if you want to form a "memory", a particular connection is strengthened. There isn't a concomitant loss of another connection. It's not a zero sum game.

All my statements are based on my understanding of mammalian learning and memory. But I think you hit on the key with "Perhaps her neurons are different".

Indeed, invertebrate neurons are wildly different from those of mammals. In fact, if you are accustomed to looking at mammalian neurons [1], invertebrate neurons can look positively alien. For example, check out the Lobula Giant Movement Detector (LGMD) neuron of the locust [2] and other insects [3].

A) The scale is different: The thickness of some of its branches are about the size of the cell body on a mammalian neuron.

B) The organization is different: The dendritic arbor is divided into nearly independent subfields with very independent functions.

C) The behavior is different: The spike output patterns of an LGMD would be distinguishable to a first-year neuroscience student. And the output connections are extremely strong, pretty much one-to-one.

Add it all together, and this one neuron does the job of at least a few dozen mammalian neurons. How many, exactly, is difficult to tell. Not every insect neuron is as fantastical as the LGMD, but I would say that "600000" value ought to be scaled by some number greater than five. Given that, one could say our spider friend has the equivalent of several million mammalian neurons.

Raw neuron count is merely the crudest of measures of neural processing capability. How sophisticated the processing nodes are (i.e., the neurons) and how they are wired together (i.e., the network topology) are way more critical.

[1] Note that http://en.wikipedia.org/wiki/Neuron depicts exclusively mammalian neurons.

[2] Locust version: http://jn.physiology.org/content/97/1/159/F1.large.jpg ; figure from this article: http://jn.physiology.org/content/97/1/159.full

[3] Fly version, top row; rat (i.e., representative mammalian neurons) for comparison, bottom row: http://c431376.r76.cf2.rackcdn.com/995/fnsys-03-017/image_m/... ; figure from this article: http://www.frontiersin.org/systems_neuroscience/10.3389/neur...