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Thinking Machines

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Published a white paper. It describes in a nutshell the hierarchical memory-prediction framework (they call it Hierarchical Temporal Memory) put forth in the On Intelligence. It also gives out a lot of interesting implementation details on how learning and prediction works. The hints on using HTMs for different applications are also thought-provoking. Posted by Trucza Csaba at 2:11 PM. Links to this post. Then w...

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Thinking Machines | thinkingmachines.blogspot.com Reviews

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We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Published a white paper. It describes in a nutshell the hierarchical memory-prediction framework (they call it Hierarchical Temporal Memory) put forth in the On Intelligence. It also gives out a lot of interesting implementation details on how learning and prediction works. The hints on using HTMs for different applications are also thought-provoking. Posted by Trucza Csaba at 2:11 PM. Links to this post. Then w...

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Thinking Machines | thinkingmachines.blogspot.com Reviews

https://thinkingmachines.blogspot.com

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Published a white paper. It describes in a nutshell the hierarchical memory-prediction framework (they call it Hierarchical Temporal Memory) put forth in the On Intelligence. It also gives out a lot of interesting implementation details on how learning and prediction works. The hints on using HTMs for different applications are also thought-provoking. Posted by Trucza Csaba at 2:11 PM. Links to this post. Then w...

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thinkingmachines.blogspot.com

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Thinking Machines: 2004-12

http://www.thinkingmachines.blogspot.com/2004_12_01_archive.html

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. A predictor has an input vector (I = {i0, i1, ., in}). A predictor learns patterns appearing on these inputs. A pattern can be:. A subset of I. A sequence of I's. A sequence of a subset of I. A shifted/broken up sequence of a subset of I. The patterns recognized are assigned a new symbol. A predictor has an output vector (O={o0, o1, ., on}). Otherwise it outputs the original signal. The link between predictors c...

2

Thinking Machines: 2005-04

http://www.thinkingmachines.blogspot.com/2005_04_01_archive.html

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Last night I watched my six-year old son sleeping. Besides the fact that it is aesthetically pleasing to watch a six-year old sleeping (especially if he is your son), it's puzzling. Why do we sleep? Why do we dream? And of course I have an idea of mine about this: it's about sorting out the day's happenings. I think it goes something like:. We should devise experiments for these. Posted by Trucza Csaba at 1:59 PM.

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Thinking Machines: 2005-02

http://www.thinkingmachines.blogspot.com/2005_02_01_archive.html

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Humans forget things. And they remember things long forgotten. I think this forgetting-thing is important. It gives us a hint on how the brains works not. It is definitely not an index. Or a persistent storage. It's all about patterns. And if a pattern does not match your query (or to be more precise the match is not good enough) you don't remember that thing. But if the pattern is close enough, you'll get it.

4

Thinking Machines: 2005-03

http://www.thinkingmachines.blogspot.com/2005_03_01_archive.html

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Think about the memory-prediction framework: it's all layers over layers over layers of simple predictor elements. What a simple predictor does? Gets input from a lower layer, recognizes spatial and temporal patterns and passes up a new signal. I assert that the passed up signal is a simpler/ more compact representation of the received (and recognized) pattern. And what we know about compression?

5

Thinking Machines: 2005-01

http://www.thinkingmachines.blogspot.com/2005_01_01_archive.html

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. The future of the search engines. As the technology behind indexing and searching will evolve, we will probably have context-aware semantic searches. These new technologies will need new ways for searching. Keyword search is determined by the keyword based indexing of the information. The new technologies will probably allow (or even require) other means of specifying what I am after. Links to this post. You can...

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thinkingmachines.blogspot.com

Thinking Machines

We don't have machines that think, we have machines that do. - Jeff Hawkins, On Intelligence. Published a white paper. It describes in a nutshell the hierarchical memory-prediction framework (they call it Hierarchical Temporal Memory) put forth in the On Intelligence. It also gives out a lot of interesting implementation details on how learning and prediction works. The hints on using HTMs for different applications are also thought-provoking. Posted by Trucza Csaba at 2:11 PM. Links to this post. Then w...

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Welcome to Thinking Machines Consultants Ltd

Welcome to Thinking Machines Consultants Ltd.

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Forward thinking technology solutions for Enterprise Financal Services organisations. Site currently under construction].