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expert2014
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Hppy
expert2014   5/4/2014 12:20:47 AM
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Defiunitely this is a complicated system as Brain Emulator involve mental analysis. - BentleyForbes

krisi
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Re: 100,000x
krisi   5/3/2014 4:34:18 PM
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analog computation is the only way to go...otherwise you need a nuclear power plant to power all Google servers to solve the equivalent problem...brain does it on 20W thank you very much

goafrit
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Re: Interface to real world
goafrit   5/3/2014 4:18:33 PM
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>> How does it interface to real world? Do they have millions and billions of distributed sensors too?

You will need electrodes wired into the brain. But that is another research area. I think the key is building the brain first. The next will be how to get it connect to the natural one.

goafrit
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Re: 100,000x
goafrit   5/3/2014 4:17:14 PM
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>> It seems that a large portion of the savings come from being application specific and using analog computation.

Yes it is analog computation but a different beast of analog computation. You are looking at weak inversion biasing of transistors which gives you low power but you have to deal with lots of noise issues in your design.

goafrit
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Re: Neurons, neurons everywhere
goafrit   5/3/2014 4:15:36 PM
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>> But since Google has already simulated a 10 billion simplified neuron system on only 16 GPU's and used it fr computer vision one has to wonder whether simplified neurons will do

Google did that using FPGA and massive computing power which adds not a lot of value when compared to the real brain. We are not talking of having a datacenter to power your brain. We want something less power hungry and efficient that is close to the natural one. That is the innovation in Kwabena's work.

goafrit
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Re: 100,000x
goafrit   5/3/2014 4:13:26 PM
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>> 100,000 times more energy efficient, amazing...congrats Kwabena! maybe it is time for you to give a talk at emerging technologies conference 

Kwabena is such a big fella to get invitation this way. He is truly leading the neuromorphic nexus. The path to human immortality could start this small as after cloning the brain in a circuit, the next phase will be making it to replace the one we have in case one needs a better one.

_hm
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Interface to real world
_hm   5/3/2014 3:54:57 PM
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How does it interface to real world? Do they have millions and billions of distributed sensors too?

Paul A. Clayton
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Re: 100,000x
Paul A. Clayton   5/3/2014 12:58:14 PM
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The relatively low power consumption is not quite as incredible as it sounds. It seems that a large portion of the savings come from being application specific and using analog computation.

That is not meant to diminish the achievement. There seems to be significant potential use for analog (and other approximate) computation and special purpose design. Not only could the Neurogrid device be useful in studying biological systems, but the project's work on hardware and software design might help advance use of similar systems for other areas.

alex_m1
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Neurons, neurons everywhere
alex_m1   5/3/2014 12:16:57 PM
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This is definetly asn interesting project, and it will surely be useful for learning more about the brain.

But since Google has already simulated a 10 billion simplified neuron system on only 16 GPU's and used it fr computer vision one has to wonder whether simplified neurons will do , or we really need complex neurons for engineering applications ?

krisi
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100,000x
krisi   5/2/2014 8:05:59 PM
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100,000 times more energy efficient, amazing...congrats Kwabena! maybe it is time for you to give a talk at emerging technologies conference (www.cmosetr.com)...kris.iniewski@gmail.com



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