Is DNA the Blueprint of Intelligence?

[apeiron]

Every single measurement/prediction has complied to physical law thus far e.g. evolution of the wavefunction complies to the shrodinger equation, planets move in their orbits according to einsteinian geometry (although this is just an approximation, really). What observation hasn't conformed to physical law?

We have a collection of partial models of reality and no complete theory of everything.

As you have said, QM lacks a story on the observers that give meaning to the wavefunction. Einstein offered higher accuracy than Newton, but is gravity a force, spacetime curvature, or what?

So you can't argue that there is a completeness about physical theory which makes it certain higher level emergent properties of complex systems can be broken down to "pure physics".

You ought to read Schroedinger's What Is Life? for a classic text making the case that "biology is larger than physics".

Theoretical biology is concerned with things like theories of meaning. I realize most other physicists seem to be on a mission to erradicate such things from scientific modelling.

Which is why we hear so much rubbish on issues like freewill, consciousness - and here, intelligence.

 

[apeiron]

Evolution, properly, is not "learning". If it gets cold and 50% of your single celled species dies out because they were unable to survive the weather change it is not because they did not learn something and the other 50% did not survive because they had learned something.

Wrong. Learning does involve the elimination of information. Babies have a proliferation of synapses and prune to fine-tune.

We learn skills like driving by learning what features of the environment to ignore.

Individuals may reproduce with variable success. But the species genome as a whole is the entity to which we would attribute adaptive or anticipatory change - learning or intelligence in every day language.

 

[apeiron]

...for the purpose of survival.

Again, the purpose is better thought of in terms of the second law. Life is dissipative structure whose purpose is accelerating the degradation of entropy gradients.

http://www.nesh.ca/jameskay/www.fes.uwaterloo.ca/u/jjkay/pubs/Life_as/lifeas.pdf

http://www.library.utoronto.ca/see/SEED/Vol2-3/2-3%20resolved/Salthe.htm

http://www.mso.anu.edu.au/~charley/papers/LineweaverEgan2008v2.pdf

 

[TheStatutoryApe]

Wrong. Learning does involve the elimination of information. Babies have a proliferation of synapses and prune to fine-tune.

We learn skills like driving by learning what features of the environment to ignore.

Individuals may reproduce with variable success. But the species genome as a whole is the entity to which we would attribute adaptive or anticipatory change - learning or intelligence in every day language.

As I noted, the 'intelligence' would have to be attributed to the species as a whole. An individual specimen of DNA or any single cell would not necessarily be considered 'intelligent' in and of itself. It would be like calling a punch card 'intelligent'. And I still think that there are issues with attributing 'intelligence' in this fashion. Pruning information in and of itself can not be considered 'intelligence' I do not think. Nor would I consider random mutation and accidentally novel combinations of genes to be the acquisition of information.

 

[JoeDawg]

But the species genome as a whole is the entity to which we would attribute adaptive or anticipatory change - learning or intelligence in every day language.

Genomes don't anticipate.

 

[noblegas]

I think that intelligence is the application and understanding of knowledge. knowledge is just knowing a bunch of facts but not necessarily how those facts have arise or why they exist. knowledge is trivial ; By trivial, I mean knowledge is what you would memorize for a trivia contest like jeopardy. an intelligent person would understand how the pythagorean theorem is derived, not just tha the pythorgeroean theorem is known by the equation a^2+b^2=c^2

 

[apeiron]

Genomes don't anticipate.

How do they know the kind of body you would need then?

Encoding for a pair of legs, for example, is a prediction about something.

 

[TheStatutoryApe]

How do they know the kind of body you would need then?

Encoding for a pair of legs, for example, is a prediction about something.

How is reading code anticipatory?

 

[apeiron]

How is reading code anticipatory?

The code is the anticipatory statement.

 

[JoeDawg]

The code is the anticipatory statement.

That's what you call an abuse of teleology.

The code exists through random mutation and natural selection, not design or purpose.
Genomes don't think, you're anthropomorphising.

 

[apeiron]

That's what you call an abuse of teleology.

The code exists through random mutation and natural selection, not design or purpose.
Genomes don't think, you're anthropomorphising.

No it is a generalisation of a psychological term towards a general physical meaning.

This is what is happening out there in a world which you may not be aware of.

From semiotics we move to biosemiotics and hopefully eventually to pansemiotics.

This is current work within theoretical biology.

You may object, but it would help if you read the references first.

 

[JoeDawg]

You may object, but it would help if you read the references first.

What you describe is an abuse of teleology, pure and simple.

As to your references, and whether they actually support what you claim, you haven't convinced me it would be worth my time.

 

[apeiron]

What you describe is an abuse of teleology, pure and simple.

As to your references, and whether they actually support what you claim, you haven't convinced me it would be worth my time.

Statements - even restated - don't make an argument. And why even start conversations when you have no follow through? A very weak response.

 

[JoeDawg]

A very weak response.

You get what you pay for.

 

[apeiron]

You get what you pay for.

I'm sure that would be wounding if it made sense.

 

[apeiron]

Further examples of actual papers that some cannot be bothered to read because their views are already decided...

http://bib.oxfordjournals.org/cgi/reprint/2/3/258

With the availability of quantitative data on the transcriptome and proteome level, there is an increasing interest in formal mathematical models of gene expression and regulation. International conferences, research institutes and research groups concerned with systems biology have appeared in recent years and systems theory, the study of organisation and behaviour per se, is indeed a natural conceptual framework for such a task. This is, however, not the first time that systems theory has been applied in modelling cellular processes. Notably in the 1960s systems theory and biology enjoyed considerable interest among eminent scientists, mathematicians and engineers. Why did these early attempts vanish from research agendas? Here we shall review the domain of systems theory, its application to biology and the lessons that can be learned from the work of Robert Rosen.

The work of Robert Rosen is important in that he not only identified
the weaknesses of our common approach to represent natural systems but he also
outlined a possible way to transcend the reactive paradigm in order to obtain
representations of anticipatory systems.

One of Rosen's achievements is that he introduced a formalism rich enough in entailment to allow final causation without implying teleology. The conceptual framework in which he developed his relational biology is category theory.

His conceptual framework arose from a criticism of the transfer of principles of Newtonian physics to biology. It is in this context that his work deserves renewed interest in the postgenome era of biology and bionformatics. One of the challenges for the emerging field of systems biology is then to link abstract mathematical models, like for example (M,R)-systems, to specific current problems of genomics. An important difference from the 1960s is the availability of three types of gene expression data at different levels: genome level (sequences), transcriptome level (microarrays) and proteome level (mass spectroscopy, gel techniques).

 

[apeiron]

http://www.zbi.ee/~kalevi/textorg.htm

Signs appear as a result of the categorisation process which takes place with the interaction of texts. This can be interpreted as a primary form of anticipation learning. The behaviour of the sequential organic molecules with a high combinatorial potential gives rise to several features which are isomorphic with those of semiotic systems, and text. Organism is a text to itself since it requires reading and re-presentation of its own structures for its existence, e.g., for growth and reparation; it also uses reading of its memory when functioning. This defines an organism as a self-reading text. Anticipation is a property which primarily appears in autocatalytic cycles. For textual autocatalytic systems, anticipation could be represented as a sign.

 

[JoeDawg]

http://www.zbi.ee/~kalevi/textorg.htm

Well of course there is a teleology to biological replication.
But evolution is more than just replication.

Genomes don't select for two legs, all they do is implement a selection. The 'selection' for two legs, happens because of a random mutation, and then enviromental pressure, within populations(not genomes).

Its only after the selection process, that you get a coherent implementation of genomic 'text'.

I don't think your refs are saying what you seem to think they are.
And if those other refs are, I think they are wrong.

 

[binbots]

Is it not possible to see oursleves as AI instead of intellegent. I mean if we create a robot with AI would he not ask and seek all the questions and answers we do. WHo create me? Where did I come from? etc. I see us as amazing biological machines designed by our cells for our cells. The machine became so advanced that it started to question its own existence and thought of itself as a single being. Even though we know we are made up of cells and even more bacteria. Just like evolution gave us legs and eyes, we with this AI survived and began to know things that our cells could not comprehend. We are not smarter just have better tools to observe. Just like if we create AI machines they will start to understand things bigger than us. Intellegence is not something that can be measured. It just is survival of the WHOLE SYSTEM of evolution.

 

[apeiron]

Well of course there is a teleology to biological replication.
But evolution is more than just replication.

You are mixing up development and evolution. Modern biology is learning how to make that distinction. That is the point of Rosen's MR systems for example.

If you are to generalise psychological notions like intelligence to DNA - which was the OP - then intelligence is displaying adaptive behaviour. Adaptation of mental states involves the two aspects of ideas and impressions, anticipations and learning. There is a cycle of activity, an interaction between expectations and what happens.

To apply this to DNA, we would have to shift scale from individuals to the species level of adaptation of course. So the genome is that generalised scale of intelligent and responsive knowing.

Anticipation then relates to the developmental aspects. Learning would be selection - across many individuals and many generations.

You perhaps still want to say the selection, the learning based on "random" mutations come first. But it is really the anticipations that provide the context for any learnings. The output precedes the input - which is what non-systems thinkers feel is so "wrong".

And I say "random" as randomness is always the product of constraint. Genetic variety is gaussian - constrained to a single scale. Unbounded variety is more likely to show a geometric mean. So again, a prediction is being made via anticipatory constraint.

An excellent paper on the patterns of nature is...
http://stevefrank.org/reprints-pdf/09JEBmaxent.pdf

 

[apeiron]

Is it not possible to see oursleves as AI instead of intellegent. I mean if we create a robot with AI would he not ask and seek all the questions and answers we do.

The desire to see all reality in terms of machines continues to be science's biggest philosophical error.

Machine models can be useful - for making machines for example. But the problem displayed over and over in these forums is the inability to think about nature in any other terms.

 

[JoeDawg]

You perhaps still want to say the selection, the learning based on "random" mutations come first.

Yup. Because evolution may have feedback loops, but it progresses linearly.

 

[apeiron]

Yup. Because evolution may have feedback loops, but it progresses linearly.

Which invalidates the idea that anticipation precedes learning how?

 

[JoeDawg]

Which invalidates the idea that anticipation precedes learning how?

Sigh.

 

[apeiron]

Sigh.

Sigh away. Beats having to support your quick assertions with arguments and citations. At least you are aware now there is a rather large literature on these issues.

 

[JoeDawg]

Sigh away. Beats having to support your quick assertions with arguments and citations. At least you are aware now there is a rather large literature on these issues.

Your 'citations' don't seem to support your claims...
All you did is regurgitate half-digested ideas and then repeat them.

Do you really expect anyone to take that seriously?

 

[apeiron]

Your 'citations' don't seem to support your claims...

That is a serious accusation. I think you should either retract it or demonstrate how they fail to demonstrate the fact there is a move to generalise psychological notions such as anticipation to a systems biology approach.

 

[JoeDawg]

That is a serious accusation. I think you should either retract it or demonstrate how they fail to demonstrate the fact there is a move to generalise psychological notions such as anticipation to a systems biology approach.

I've already responded to your claim and your citations.
This is the part where you explain its all based on a dichotomy.

 

[apeiron]

I've already responded to your claim and your citations.
This is the part where you explain its all based on a dichotomy.

Another cop out reply. A series of unsupported smart arse one liners do not make a "response".

And yes of course it is all based on dichotomies. Haven't you noticed that already?

Evo-devo. Category theory. M-R systems. Anticipation and learning. What else are the cited sources talking about?

And also triadics. Peircean semiotics and hierarchy theory.

A symmetry is monadic. Breaking a symmetry is dyadic. Mixing the broken symmetry is triadic. It really is as simple (and complex) as 1,2,3.

As I say, your problem is that you are stuck in a materialist discourse. Only monadic models compute. The sound of one hand imagining it is clapping.

 

[Klockan3]

Apeiron, just because they use a model which treats genome as intelligent do not mean that it is by the standard definition. Saying that genome is intelligent since it produces viable species is like saying that water is intelligent since it always bunches up in such a way as to minimize its potential energy! Clearly since water can solve such hard problems it must be intelligent! And even if you change the attributes of the system water have anticipated this sort of behavior and thus always adapts to any new configuration you might imagine in an instant!

 

[apeiron]

Apeiron, just because they use a model which treats genome as intelligent do not mean that it is by the standard definition. Saying that genome is intelligent since it produces viable species is like saying that water is intelligent since it always bunches up in such a way as to minimize its potential energy! Clearly since water can solve such hard problems it must be intelligent! And even if you change the attributes of the system water have anticipated this sort of behavior and thus always adapts to any new configuration you might imagine in an instant!

Correct. That is what pansemiosis would be. You start at the other end of the problem for a change. Instead of trying to build upwards from dead materials, you go the other way from mental terminology. You take a term like intelligence, or better yet anticipation, and see how it applies to psychology, then biology, then chemistry and physics.

A system with scale does anticipate its future states in some meaningful sense. Once water has formed up into a droplet bound by surface tension, it will carry that state forward into the future, resisting perturbations (up to a point). It becomes a system with a memory.

We could call it something different so that we not accused of some kind of spooky mentalism - hysteresis for instance.

Or we can actually work backwards from complexity to discover simplicity.

A flexible mind has no trouble working in either direction and gets used to modelling in both.

 

[binbots]

Why don't we look at intelligence from a bigger perspective. If we all agree of the rules of evolution then survival and reproduction are the guide lines for defining intellegence. By those standerds we are actually pretty dumb. Humans have not been around very long and we seem to believe that we are on the brink of extiction. If you take reproduction then insects win the battle.

 

[binbots]

If you say that we are smart becuase of say math you forget that math is something we made. You can not judge something you created for it will be bias. If ants could make large machines and weapons and then they blew themselves up would we consider them smart?

 

[apeiron]

Why don't we look at intelligence from a bigger perspective. If we all agree of the rules of evolution then survival and reproduction are the guide lines for defining intellegence. By those standerds we are actually pretty dumb. Humans have not been around very long and we seem to believe that we are on the brink of extiction. If you take reproduction then insects win the battle.

I think you have to separate out the notions of adapted and complex still. One is a measure of the system's equilibrium balance, the other of its sheer intricacy and variety.

So the big question about humans is how much we are an out-of-equilbrium fluctuation, soon to be corrected (whereas insects as part of ecosystems are more "intelligently" adapted - they would score higher on the in-equilibrium measure, and the question then is that what you really mean by intelligence?)

Then there is the separate notion of complexity. This can be measured by the number of different states an anticipatory system can access. Clearly, the human mind can access many more states of memory, imagination, expectation, planning, than even a co-ordinated insect colony, a group mind like an ant or bee colony.

We could also count neural complexity as a surrogate measure of mental complexity. The human brain has something like 1000 trillion connections all shaped by personal history. It is the densest occurence of systems complexity in the known universe.

So if intelligence is measured in terms of anticipatory complexity, humans win hands down.

Putting it all together, we can say that hominids were both at the top of the tree in anticipation terms and also in equilbrium with their environment up until about 100,000 years ago.

Then we broke free of a balanced biological situation with the invention of grammatical speech and the new thing of cultural evolution. Something only humans have.

So we became log/normal. On an exponential growth path against a linear environment. Out of equilibrium. We can see this in terms of population growth, oil consumption, rare Earth consumption, any measure of entropification really.

Our invention of language (memes on top of genes) was a phase change for Earth ecology. It took the biosphere into a new space. The question is what will be left when the new system, a combination of genes and memes, settles to its eventual equilbrium balance, as it must.

Some dream of Kurzweil's singularity. Others would be less optimistic.

 

[Kajahtava]

Most people here seem to work on the assumption that intelligence exists (whatever that means). That human beings who simplify and abstract reality to better cope with it experience such a concept is no guarantee to its existence, and I am sceptical towards its supposed existence.

I believe that if you experience a certain concept but cannot come to a definition of it in hard terms that can be objectively tested and verified you most likely deal with a concept that has no place in serious naturalistic science and instead deal with a concept that human beings subconsciously invent to better deal with the complexity of the world around them, you know, like 'chair' or 'evil'.

It also seems that human narcissism seems to make us hold ourselves as the one 'sentient', some linguistics think that 'human', 'man', 'manus' and 'mind' ultimately come from from one and the same origin I believe. Then there's also stuff like the mirror test which is really nazi science and as shaky as Hitler's attempts to prove the superiority of the German people. If people being able to recognise themselves in the mirror is a proof of their 'self awareness' then likewise it's a proof that humans are not self aware but dogs are because they can recognise themselves from the scent of their piss while humans can't.