Warning: This book contains a symbolic model associated to the basic hardware function of the brain. A symbolic model is a model based on logic only. So, this book is not recommended to individuals who has the tendency to understand the external reality based on imagination. The book can be understand by persons between 12 and 20 years old who have special abilities in the field of positive sciences. Also, the book is recommended to persons who already work in the field of positive sciences (mathematicians, phisicists, engineers and so on). Copyright (C) 2004 by Dorin T. Moisa
nal reality and to predict, by simulation, the possible evolutions of the model. Because the model is associated with external reality, it is possible to predict by simulation some probable evolutions of the external reality.
We already used the term "external reality" which is not defined yet. This fundamental term is considered as a source of information, which is not localized in the structure of models of the brain. I want to emphasize that the external reality is not a source of information, but is just considered so by any brain.
Thus, one of the main hardware functions of the brain is to make models of the external reality and to predict, by simulation on the model, the possible evolution of the associated external reality.
We already defined the reality as all the information which is or could be generated by a model. This means that we understand the external reality by the reality, which is generated by a model, which is associated with the external reality.
Example: For a given external
Any point of view about my book is welcomed, but, as long as you don't use the MDT terminology or at least the MDT frame, I am not convinced that you read/understand MDT.
The application section contains the MDT interpretation of some facts from the external reality and also many predictions. It is recommended to read this section after you read/understand the main theory. In this section I used a mixture of common language terminology and MDT terminology. For instance, in the common language terminology, the elephant has a huge memory, but in MDT the elephant is able to build and operate long_range_pure_image_models. What about your statement that the data/facts do not depend on the terminology?
I am sorry to see you have not understood my criticism. It seems quite plain and clear to me, so I am at a loss to why this is.
Also, you misunderstand the nature of my book-review. I did not expect or even ask for a reply from you, and I surely do not intend to use "MDT terminology" in my book-reviews. In short: a book-review is not written to chat with the author.
One more thing I want to point out: It was _you_ in exactly this book, who used the term 'elephant memory', which is ... how do you phrase it... "not defined in MDT".
PS. feel free to read it again, though - it might be harsh criticism, but there's a lot of good and useful advice there between the lines for someone willing to see it.
If I would had written a book about Quantum Mechanics, to comment it, you should have been a specialist in Quantum Mechanics. That is, you should have used Quantum Mechanics terminology. On the other hand, you comment my book without using MDT terminology. Moreover, you use terms which are not defined in MDT, such as "memory" or "neuron". I will reply to you at the moment when your comments will be based on MDT terminology. What I saw is that your terminology is based on undefined terms and that you don't see the importance of the precise definitions of MDT terms and also the precision of the relations between them.
Summary: don't bother reading, this is not a free scientific textbook, but something someone wrote/made up in his spare time and couldn't publish anywhere else.
This is a non-scientific book which pretends to be scientific. One indication of this is the total lack of citations. The author reasons in the book that it describes a fundamental model and hence does not need citations. This might be correct if he would just develop the model. Yet, perhaps 80% of the book are examples that try to apply the model (in a quite repetitive way) to "reality" - or what the author thinks is reality.
All these examples use "data" out of thin air. For some of them one could say that the data is self-evident (as we all own a brain and can check on ourselves), on others it is not. This is, e.g., the case for all comparisons to animal brains. Just to name one: the model is applied to an elephant which has a big brain, but (apparently) isn't very intelligent and has an 'elephant-memory'.
Do elephants really have a good memory? Folklore says so - but folklore is often wrong. This is where a citation would be needed. (Actually, from memory, it is also not the mass or size of a brain that make up complexity/intelligence, but the amount of neurons - and would you bet an elephant has more neurons? All this the author would have found out had he bothered to check the literature)
The reasoning that this book would be the first to define clear terms and hence is incompatible with previous publications is just a lame excuse - many interesting and intelligent experiments were done whose results can/should, no MUST be cited - instead of the popular method of "making things up". And such experiments/observations are clearly independent of the terminology used.
The book goes on and comes to some trivial as well as some abstruse conclusions from applying the model to the random made-up data.
Sentences like "Let's summarize the European spirit." give you a hint at the type of unjustified generalizations you have to suffer on reading (I wouldn't be too sure that there is a definite general "European spirit" that could be spoken of in any scientific way)
Quote from the Gutenberg project pages:
"In fact, Project Gutenberg approves about 99% of all [...]eBooks [...]"
The book was obviously "published with Gutenberg", because publishing it in this form in any peer-reviewed way would only yield the answer "unsuitable for publishing"
The model itself might be interesting - although there is never a rationale given, why a new layer, e.g. a ZM models had to be introduced (and why is the simplest "image" model an M-model?! why not an I-model? - The naming is also done without rationale or reason), but the way it is applied to rather random made-up claims is certainly not suitable.
A very good and exciting book.
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