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While I think the presentation was interesting it was fundamentally just more proof that "the brain has patterns". Wish that the talk had more depth in terms of

by vesche 12y ago

While I think the presentation was interesting it was fundamentally just more proof that "the brain has patterns". Wish that the talk had more depth in terms of understanding or implementing artificial neural networks. Understanding that the presentation was primarily to endorse Spark to more data mining applications however, the talk seems successful.

frozenport 12y ago
>>terms of understanding or implementing artificial neural networks There is no motivation for a connection between artificial and biological computational networks. A production ANN such as those used by missile interception systems is not requires to match what the neurons in your brain do. In fact, the biologists may find that our brains are not very efficient and often make mistakes. As a practical matter, the behavior of neurons is still up for debate with many models of interaction proposed. There are often more effective models for machine learning, especially if you have lots of data, such as Random Forest.
- vesche 12y ago
  >>There is no motivation for a connection between artificial and biological computational networks. I would disagree, and say that future ANN research has high motivation to become as powerful and complex as BNNs. And I think maybe you get ahead of yourself by saying that our brains are not very efficient when the fastest supercomputer we currently have built is still 100,000x less computationally powerful than a human brain. http://www.wired.com/images_blogs/wiredscience/2013/05/neurologist-markam-human-brain3_f.jpg http://www.wired.com/images_blogs/wiredscience/2013/05/neuro... "Neural Networks attempt to bring computers a little closer to the brain’s capabilities by imitating aspects of information in the brain in a highly simplified way. Although neural networks as they are implemented on computers were inspired by the function of biological neurons, many of the designs have become far removed from biological reality." http://scholarsresearchlibrary.com/EJAESR-vol2-iss1/EJAESR-2013-2-1-36-46.pdf http://scholarsresearchlibrary.com/EJAESR-vol2-iss1/EJAESR-2...
- closetnerd 12y ago
  >There is no motivation for a connection between artificial and biological computational networks. Not sure what you mean by "connection", but there is a huge motivation for understanding the biological. The neocortex is the single best implementation of intelligence we know. You should watch a couple of video talks by Jeff Hawkins which are REALLY convincing. His work on sparse distributed representation is, in my opinion, one of the biggest recent break throughs in artificial intelligence that was directly achieved by researching the neocortex.

by vesche 12y ago

frozenport 12y ago

>>terms of understanding or implementing artificial neural networks There is no motivation for a connection between artificial and biological computational networks. A production ANN such as those used by missile interception systems is not requires to match what the neurons in your brain do. In fact, the biologists may find that our brains are not very efficient and often make mistakes. As a practical matter, the behavior of neurons is still up for debate with many models of interaction proposed. There are often more effective models for machine learning, especially if you have lots of data, such as Random Forest.

vesche 12y ago
>>There is no motivation for a connection between artificial and biological computational networks. I would disagree, and say that future ANN research has high motivation to become as powerful and complex as BNNs. And I think maybe you get ahead of yourself by saying that our brains are not very efficient when the fastest supercomputer we currently have built is still 100,000x less computationally powerful than a human brain. http://www.wired.com/images_blogs/wiredscience/2013/05/neurologist-markam-human-brain3_f.jpg http://www.wired.com/images_blogs/wiredscience/2013/05/neuro... "Neural Networks attempt to bring computers a little closer to the brain’s capabilities by imitating aspects of information in the brain in a highly simplified way. Although neural networks as they are implemented on computers were inspired by the function of biological neurons, many of the designs have become far removed from biological reality." http://scholarsresearchlibrary.com/EJAESR-vol2-iss1/EJAESR-2013-2-1-36-46.pdf http://scholarsresearchlibrary.com/EJAESR-vol2-iss1/EJAESR-2...
closetnerd 12y ago
>There is no motivation for a connection between artificial and biological computational networks. Not sure what you mean by "connection", but there is a huge motivation for understanding the biological. The neocortex is the single best implementation of intelligence we know. You should watch a couple of video talks by Jeff Hawkins which are REALLY convincing. His work on sparse distributed representation is, in my opinion, one of the biggest recent break throughs in artificial intelligence that was directly achieved by researching the neocortex.