- File Size: 1138 KB
- Print Length: 105 pages
- Page Numbers Source ISBN: 1511617020
- Simultaneous Device Usage: Unlimited
- Publisher: Kios Press; 1.1 edition (April 9, 2015)
- Publication Date: April 9, 2015
- Sold by: Amazon Digital Services LLC
- Language: English
- ASIN: B00VXGFBI6
- Text-to-Speech: Enabled
- Word Wise: Enabled
- Lending: Enabled
- Amazon Best Sellers Rank: #465,090 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
|Print List Price:||$5.40|
Save $3.90 (72%)
The Relativistic Brain: How it works and why it cannot be simulated by a Turing machine Kindle Edition
|Length: 105 pages||Word Wise: Enabled||Enhanced Typesetting: Enabled|
|Page Flip: Enabled||
Matchbook Price: $0.00
For thousands of qualifying books, your past, present, and future print-edition purchases now lets you buy the Kindle edition for $2.99 or less. (Textbooks available for $9.99 or less.)
Try Kindle Countdown Deals
Explore limited-time discounted eBooks. Learn more.
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter your mobile phone number.
Customers who bought this item also bought
Would you like to tell us about a lower price?
Top customer reviews
There was a problem filtering reviews right now. Please try again later.
If this sounds a bit vague as to how things might work in detail, it is, and it doesn’t get too much better in this respect. The role of the digital component (via the frequency spikes) in either thought, language, perception, whatever, is little explained for example, as well as other critical things I will note below. However the authors’ justification for the existence of these fields via emerging neural evidence (albeit still speculative) and the glimpse of a real alternative model of the brain emerging, is itself worth the read, as well as the several principles of brain function for which they argue (e.g., extreme context sensitivity). Also of great interest are the several chapters in the second part of the book, based on the neural view given, which are devoted to the question of whether the brain can be simulated by a digital computer, to comparisons to a Turing Machine, to implications of Gödel, and very important, to Turing’s “Oracle” machine concept as essential in a broader form of computation, the form that very possibly characterizes the brain, the entire brain being perhaps an O-machine. In the authors’ example, a protein (as a tiny O-machine) finds its optimal 3-D configuration – an intractable computational problem – in an instant by following the laws of physics in the analog domain. This entire discussion, juxtaposed, say, with something like Bostrom’s (Superintelligence, 2014) which blithely extols the future of Whole Brain Emulation via digital computer, makes the latter look very naïve. This is a must read discussion for those who have not encountered the O-machine concept of Turing and its deep significance for the nature of computation; it can be a shocking revelation re the actual power (or not) of standard Turing computation.
As to the “standard problem” in this review title: The authors argue for an “internal model” - say, of my kitchen, the table, my coffee cup and spoon stirring away – created/supported in the neural-generated space-time continuum. This is but a very weak attempt to solve Chalmers’ “hard problem” of consciousness, wherein we must explain how any neural or computer architecture explains the “qualia” of the perceived world – the silveriness of the spoon, the whiteness of the cup. This problem has been misleading, stated as it is only in terms of qualia. Even form is qualia – the stirring spoon, the squares on the tile floor. It is better understood as that of accounting, in general, for the image of the external world. There is nothing in the neural-chemical flows that looks like the kitchen with its table and coffee cup. Nor does it help to say that populations of these flows, creating EM fields, accounts for this. There is nothing about an EM field that can be made to look like a coffee cup. The authors appeal to “emergence” – the kitchen/cup “emerge” over these flows/fields - but this concept is at best a vague hope, heavily critiqued in the philosophical literature (even Yudkowsky [Rationality: From AI to Zombies, section 36], ridicules it). What is interesting though is that this EM field view sees the brain, effectively, as a very concrete device, as concrete, say, as an AC motor generating an EM field of force. It entails the brain as creating a constantly changing, constantly modulated, very concrete wave form, and this is now approaching the conception of the brain that Bergson (Matter and Memory, 1896) required to explain the problematic origin of our image the external world. Bergson had presciently envisioned the essence of holography fifty years before Gabor's discovery (unfortunately leaving his contemporaries puzzled as to his model), attributing a holographic property to the universe 85 years before Bohm (The Implicate Order, 1980). As opposed to Pribram, who later saw the brain simply as a "hologram," Bergson viewed the brain as creating, in effect, a constantly modulated, very concrete, reconstructive wave passing though this holographic field, a wave specific to a subset of the vast information in the field, the specified subset by this very process being now an image of the field – the table, cup and stirring spoon.
There is obviously more to this, but this gives an idea of what a concrete mechanism for the origin of the image of the external world might look like, as opposed to appeals to emergence and to unexplainable internal models (the latter also with myriad logical problems). To add another point of relation to the book, one will ponder exactly why the authors call their model the “Relativistic Brain,” other than on the fact that a space-time continuum is supposedly built (with internal model) and that there is global constraint (like the light velocity constraint in relativity?), via the brain’s total available energy, on the neural firing rates (or flow velocities). Yet, as Bergson noted, the image is specified at a scale of time (another, ungrasped aspect of “qualia”). A fly moving by the coffee cup is seen with his wings a-blur at normal scale. But the fly (and the cup) could have been seen as a cloud of whirling atoms, or, with a lesser change, as a stock still, motionless fly. That is, the subset of the holographic field, which has no particular scale, is specified at a scale of time. This must be a function of the brain’s very concrete dynamics, e.g., the chemical velocities underlying these neural flows (thus the EM waves). The “relativistic” aspect comes through then if one now considers introducing a catalyst into the brain, or a set of catalysts, which increase the energy available to the chemical reactions (changing the value of the global constraint), increasing the chemical velocities (and increasing the EM modulation frequencies): At sufficiently higher than normal velocities, we could expect the fly to now be specified as though heron-like, barely flapping his wings, i.e., we have a new “space-time partition.” Correlatively, as in relativity, we would now require invariance laws which hold across space-time partitions (just as d=vt or d’=vt’) to specify events, e.g., as per laws advocated by J. J. Gibson (The Perception of the Visual World, 1950).
All in all, the book, imo. is very interesting preview as to where we are perhaps going in our views of the brain, with essential, definitely to be considered critiques of the unrealistic views of AI and brain emulation.
I found the book to be pretty heavy going at times and don't claim to understand all the details of why the authors believe that the unique intelligence and self awareness of the human mind will never be emulated by a Turing machine. I do believe however that AI enthusiasts need to get to grips with the arguments that the authors present here instead of merely taking it as a given that AI will inevitably emerge as soon as we have enough computing power. If the authors are correct and minds are not computible then no matter how much computing power and speed is available the mind will never be emulated by a Turing machine because it is not possible in principle, just as an infinite number of super fast automated abacuses could never appreciate beethoven.
Being as inexpensive (I paid somewhere around $2 - $3 for the Kindle edition) and short (I believe it's only 100 - 150 pages) as it is, I believe it is worth picking up and reading—especially if you are studying neuroscience in any capacity.