I gave my talk "Logic and computation as biophysics" yesterday. Here is a picture of me making the presentation. I have an imperfect recording of the presentation that will be made available through IASE. If you are interested in access to the recording request that access through me.

Since my May update I have made numerous small revisions to my book's draft "Introductory Remarks." These revisions are mainly derived from feedback on a related submission document to SuperComputing 2011 that comes from a chapter of the book on the Foundations of Computation.

In that submission to the Disruptive Technologies Program I propose a new computational paradigm for certain large scale parallel computing problems so the reviewers were all leading Computer Scientists. This work is not generally available but I did want to propagate some of the important elements of the review back into the Introductory Remarks.

The primary additions from the review relate to some relative comments with respect to Connectionism and Neural Networks.

Honestly, despite its popularity among Neuroscientists, I had dismissed Connectionism long ago and view Neural Networks as a failed technology founded upon a model that is naive and poorly informed.

However, several senior reviewers criticized my failure to mention it directly and, worse, suggested that I had not done adequate research because it was absent.

The truth is that during the late 1980s and early 1990s, before I embarked upon this work, I spent a lot of time with the Churchland work and with McClelland's "Distributed Parallel Processing" text and thought that we had all moved on from what had become a footnote in history :-) 

This was wrong of me and I should have included Connectionism in my review, at least to compare my model of distributed representation with the earlier work.

In short, the problem with Connectionism and Neural Networks is that they were founded before a lot of the more detailed evidence became available: they are naive, not founded upon a general theory, they deal with "brains" not organisms, and they ignore physical structure.

My decomposition arguments also hold. Neural Networks do not form a computational parallelism that makes a difference since the parallelism in Neural Networks can be removed (the node computations executed in sequence) without a discernible effect upon the results.

I have started to correct my deficit in the "Introductory Remarks" and, for historical completeness, will add a discussion of Connectionism in a new section of the book. This sort of evolution is why books should always be well reviewed before publication. It's why I publish drafts of my evolving work online.

Although I get few real review comments unless I pointedly ask someone to do it. I tend instead to hear only from people that either love the work and it has changed their entire view of the world (this is nice but not especially useful) or from crazy people that claim that I have stolen their ideas. So far it turns out that such people understand neither their own work nor mine, and precedence is easily established via the Archive.org record.

I also took the opportunity over the past day or two to refine the Introductory description of the model of memory and recognition. This is mostly word craft and clean up of late night bumbling, it is now a clearer technical introduction I hope. 

On the Foundations of Information Science (FIS) list Jerry Chandler takes me to task about my claim that the Uniformity Conjecture is the necessary basis of scientific epistemology. He argues that the "necessity for irregular extension" invalidates the conjecture of uniformity and that my line of reasoning "explains virtually nothing."

Jerry is someone that I respect immensely for his occasional well-considered responses on another scholarly list, Peirce-l. But I am unconvinced by his argument.  

This is not to say that there are not such extensions and that they are not necessary for the refinement of ideas. Surely they are. But from a strictly epistemological point of view they are indicators, pragmatic and temporary aberrations that are ultimately resolvable by applying the necessary uniformity conjecture.

As I note often: If a logical reduction fails it is never an indicator of the supernatural nor is it a justification for metaphysics. It is an indicator that we must, of necessity, review the logical construction that has failed and ultimately revise it.

The central point of my argument concerning the profound uniformity of Nature is that no scientific epistemology is possible without this conjecture. If we reject it or worse, if we find evidence that the universe is not uniform in this way (by finding a galaxy that does not conform to the laws observed in the others, for example) then all bets are off and no scientific epistemology is possible.

Jerry goes on to say that "the only intrinsic uniformity is of space and time."

Since I take space and time to be merely a way of speaking about mass/energy, as did Einstein, its uniformity or not is a matter of conception alone. If you disagree with this then you essentially affirm the case I make since it is then the laws of space and time that would be the necessary basis of all science.

Jerry is concerned that my line of reasoning "excludes the mental, biological and chemical sciences." But this would only be the case if I did limit my formal conception of the world to space and time. If you have read my materials then you will know why I think that this is inadequate.

Further, for me "explanation" is the identification of causes. The notion of profound uniformity identifies the casual basis, the functional dependence, of all scientific knowledge; as such it is an explanation of why science works.

This is a follow-up to my earlier note that observes that science abandons absolute truth and that we can be okay with that. Again, this post is an echo of a discussion on the Foundations of Information Science list with Stan Salthe. The epistemology I advocate here is articulated in my forthcoming book on The Foundations of Logic and Apprehension that is outlined at senses.info.

What is the issue and why is the uniformity of the world both necessary and profound?

When I say that the uniformity of the world is "profound" I am simply asserting that this feature of the world has broad consequences, it is not "merely uniform." It is not a trivial observation. The concept of uniformity in nature underpins the whole of scientific knowledge.

If the world is not this way then we cannot make any kind of claim about the world. This profound uniformity is necessary to enable any scientific statement, without it there can be no science.

To say the world is profoundly uniform is an existential statement, not an epistemological one; yet it has direct consequences for scientific epistemology and provides its foundation.

The universe, independent of any conception, is then necessarily and profoundly uniform if we are to have any scientific knowledge.

This uniformity is the basis of perceived universals. Our conceptions can have no intrinsic uniformity, no basis for consensus, no predictive power unless they are founded upon this profound feature of the world. 

To be clear, I am not referring to statistical uniformity or probability theory but to an absolute uniformity, the uniformity underlying the world's structure.

This uniformity is that which underlies the laws and principles of our observations; it is the scientific assertion that the determinant features of the world, apprehended as laws and principles, are everywhere the same.

We must not be misled by different methods of mathematical characterization. The merits of statistics and probability theory serve, in fact, to underscore the profound uniformity of the world; they wouldn't work otherwise.

If we take the view that the probability basis of Quantum Mechanics or the Uncertainly Principle undermines the uniformity of the world, and are not simply epistemological statements involving the current or intrinsic limits of apprehension, then all bets are off; the whole of science is not only fallible, the empirical evidence is necessarily subject to arbitrary change. Empiricism relies upon this uniformity. Statistical results and probability predictions simply help us identify or finesse what we do not know.

The universe is evolving and changing between radically different states. Does this imply that scientific conceptions are only valid for a finite period? Does this uniformity persist? Profound uniformity does not suggest a static world, only that the underlying nature of the world is not arbitrary.

The profound uniformity of the existent universe is the necessary basis of scientific knowledge; without it all bets are off.

Yet this notion is necessarily a conjecture, both verifiable and fallible, but without it there can be no science.

An epistemology that rejects this view and "eschews any universal understanding," simply cannot be scientific. It is the view of disenchanted sociologists, philosophers or diplomats, perhaps.

Uniformity is easy to verify, after all we successfully sent multiple men to the moon. If you want to invalidate science you need only demonstrate one case in which the uniformity is denied. For example, find a galaxy that operates by laws that differ from others. Let me know how you get on.

In a recent Foundations of Information Science posting (FIS) I attempted to clarify the scientific theory of "Truth." Here I restate and expand that argument. 

"Truth" is simply a way of speaking about existence, it is a way of speaking about the correspondence between the apprehension of statements and the way things are or, more generally, of experience and the way things are. 

"Justified true beliefs" are today, essentially, verifiable and fallible, not absolute. This is how we now characterize Plato's appeal to "justification." 

Therefore, even science that is not strictly correct can be said to be "true." Newton's laws are true to this extent, they do correspond to the way things are, they are verifiable and fallible. That we know the extent of their fallibility is beside the point. General Relativity is simply a closer approximation, and it is also verifiable and fallible. 

Can we say then that Newton's laws are "not true" on the basis of this? If we are rigorous about it, I don't think that we can. Clearly General Relativity can be said to be closer to the way things are because the statement of it provides a broader "explanation," a boarder identification of causes. But if we do so then we must accept that "truth" is simply a matter of degree, a measure of "certainty" in our statements.

In short, the notion of "truth" has become redundant, a metaphysical notion inherited from a time when the conception of "absolute truth" seemed viable and could be imparted by an ultimate authority. In fact there is no such authority and "truth" is a meaningless notion in science unless by it we refer to "certainty," a question of degree; and at that point the notion of "truth" is obsolete, our attachment to it emotional.

The nature of "Truth" is then what Rudolf Carnap would call a "psuedo-problem" in philosophy. Science necessarily abandons all hope of absolute truth and our use of the term and hand-wringing over the notion can be comfortably put aside.