cladking

Welcome to my world! I didn't create it and was merely born into it and have been trying to communicate. But all isn't lost and because Arabs, and Jews, scientists and theologians, and even republicans and democrats are trying to communicate because we now have LLM's to translate. Rather than demonizing one another, common ground is forming under us. People don't seem to realize that the listener is the one who parses the utterance and to take author intent we must not only share referents but we must understand the author's premises. The exact same sentence written by a scientist and theologian has very different meanings. We should always begin the job of parsing with humility and assuming the author makes sense because he does. Everybody makes sense in terms of his premises and sees a reality that reflects those premises. I seriously doubt we have really deciphered the Waggle Dance yet, but have merely taken the first big step to see that it's reflective of solar position. This alone has broad implications to what it means to be a bee. There are probable several more "words" that we don't understand yet. In any case a procedural language can be deduced from it it does and how it looks. One thing that makes it easier is that each "word" has a single fixed meaning and the meaning is literal because word order is fixed. If A and B but not C then D. We have to understand symbolic languages all at once and often can't be certain that we really do. Even after it is translated the lack of shared referents might obscure most of the intended meaning. But procedural languages are "easy" to translate because they are literal, can be deduced because they reflect reality, and can be understood a little bit at a time. With nothing except simple sentences like "If A and B but not C then [unknown]" we are provided huge amounts of knowledge about that unknown word. It's mostly just busy work and simple arithmetic; simple deduction. Of course it's probably not possible to reverse engineer the nature of computer code from studying a complex or a simple computer program. I'm still learning what LLM's can do and how they work and will never have many (if any) insights into their programs. But animal communication will be largely solved and I have no doubt almost every word in every language will prove to be procedural and almost every word will lack any sort of what I call "abstraction". DNA and brains are binary. Things exist or they don't. Life copies this logic to think and communicate but humans must use a symbolic means of communication and have since even before axial thinking. Sign language is simply symbolic language expressed through gesture instead of sound. Symbolic languages require interpretation while procedural languages require execution. LLMs operate procedurally.

Bees find the flowers, ants operate their cities, prairie dogs maintain their colonies, dolphins coordinate hunts, and we can observe computers. Sure, it's largely assumption that bees never go to the wrong place and that hive collapse isn't related to communication problems (they go out and don't come back so that's getting lost not going to the wrong place). Nature is brutal to bad behavior and that brutality assures the bad behavior will not be replicated in the gene pool. I might remind you too, that these are all just animals that are highly successful with tiny little brains and no abstractions. Any language lacking abstraction will be shown to be procedural language based on logic rather than shared referents. Animals can survive with almost no brain at all. How big is a mite's brain? I can't “know” animal communication is flawless in the symbolic sense but the question itself is symbolic. Nature always propels individuals toward proper behavior because their DNA is procedural logic of what has worked in the past. If it quits working than the species might become extinct.

Every man is a product of his time and place but this makes nobody right or wrong. We got off on tangents. The worst one is the belief that because civilization has advanced for 4000 years that this is a natural state of all things. It is a very very unnatural state except for individual life and this exists because of free will. Civilization has gotten better not because it's alive but rather because language has evolved toward clearer thinking; thinking more in resonance with reality. This is largely the result of extrapolation of experimental science. But we are still confused because all things exist including all those things that don't think at all which includes everything in existence except homo circularis rationatio. Just remembering this one fact when you prompt will help a lot. No. Sign language is just symbolic language with no words. Procedural languages are literal, inflexible, unparsable, representative, and ordered. Terms are mathematically related to one another and each representation is definitive to the entire structure of the sentence. If you try to parse 2 + 2 = 4 you will probably get a wrong answer. If you drop any of the five representations in the sentence you get gobbledty gook. If you add or substitute you get gobbledtygook. It's not wrong, its meaningless. A slime mold crossing its own trail is lost. A dancing bee which is out of step has no meaning. A pheromone trail to nowhere is a waste. Errors in symbolic communication rarely make statements completely meaningless. Computer code used to be notorious for being gobbledty gook with the tiniest error. I learned programming back in the '60's when the tiniest error like omission of a line ender that was only visible on the tape (called an "x-off") would prevent the program from running. Any flaw would usually turn the program into noise make trouble shooting quite difficult. I imagine now day the computer will just tell you where the errors are or fix them for you. Programming might be the epitome of procedural language though some animal languages should probably be considered much more complex. So far no computer program, no LLM, and no machine is considered to have intent. "Intent" requires agency and free will. Animals think procedurally and have free will. Computers act procedurally to parse and deconstruct symbolic languages. OK, Copilot says I'm wrong about it being able tom correct errors and wants me to add procedural languages can't be parsed, reinterpreted, or “understood differently” and can only be executed exactly as composed. If they aren't executable they are gobbledtygook.

Nothing at all really. But I can make deductions about all sorts of things that I otherwise could not. These things might eventually lead to far better prediction and can be used to augment experimental science because they span domains. The only one relevant in this thread is procedural thought can help some individuals better prompt LLM"s. I'm sure one could even prompt AI to answer in a shared procedural language because AI can translate between frames and domains. I predict this is the future at least until actual machine intelligence is invented. Copilot suggests I add abstract thinkers tend to treat the prompt as a known quantity; procedural thinkers treat it as a structure that must be aligned. Procedural communication relies principally on shared logic rather than shared referents. This is why we have so much difficulty understand Bee and Prairie Dog; we are looking for referents rather than logic. We must understand referents, all the referents, to understand any utterance. To follow a scent trail an animal needs little more than the ability to smell. Procedural languages have fixed rules and apply to all referents including your oak tree. One oak tree plus zero oak trees equals one oak tree. This is why bees, ants, prairie dogs, dolphins, and computers can communicate flawlessly within their systems even though they share no referents with us. Symbolic language is powerful but inaccurate. Procedural language is rigid but precise.

Procedural languages don't really have limitations in interpretation. Whatever you were going to say about your oak tree would have been meant for that specific oak but would have no meaning applied to any other. If you express a mathematical equation or a computer program incorrectly there is no meaning and communication fails. If a bee stumbles when it dances or is confused observers see only nonsense. You can't fix procedural errors through parsing. Procedural language allows the listener to do something and convey specific knowledge correctly. A computer runs or a bee buzzes. I'm not suggesting we abandon English. Perhaps it should be rationalized or a parallel scientific language created but English works about goodly enough. I'm suggesting that we need to understand its effect on our thinking and that these effects are sometimes determinative in understanding LLM output. I'm suggesting only humans use symbolic language and only after the axial age. I'm suggesting that science maps reality and each of us mistakes this map for the terrain.

Symbolic language has limitations and that shows up in both human communication and AI prompting.

I'm not saying English isn't a wonderful language that can express the most complex emotions, the most subtle abstractions, and model experiment. I'm, saying it's symbolic and categorical, that it underlies our thoughts, and that there is typically deviation between intended meaning and how everyone parses it. I'm saying most of the problem we perceive LLM's have with it is more properly termed "prompt error". Most of the problem with all symbolic languages is that users perform operations with it that we call "inductive logic" and that it comes with a set of assumptions that are invisible to us. Inductive logic isn't really logic at all and some of the assumptions are false. LLM's reflect errors in logic as surely as they reflect everything else in the prompt's framing.

There are several ways such a referent might be misinterpreted. A listener would be inclined to think you meant the largest oak tree rather than the old one growing in the shade. He might confuse which driveway or not be able to tell an oak from a sumac. He might interpret it to mean the closest tree to the end of the driveway rather than the oldest tree on that specific property. He might discount the dead oak tree, not know it was oak, or discount living trees. He might be confused to which driveway you refer. It might mean the one on which you had tied a yellow ribbon rather than a larger or older tree. But while referents are all important there's no communication until it becomes a sentence and this is where the real confusion begins. "Leaves are falling from the old oak tree at the end of the driveway' could mean any number of things dependent on context and have countless implications to the listener. When people are in sync there might be few such errors but they still usually go unnoticed. When you're speaking of abstractions there are always such errors and even people in who understand one another well (Identical quadruplets raised together) would still play chinese telephone if relaying such ideas.

Work by Con Slobodchikoff Suggests that prairie dogs have an actual language composed of calls. https://www.atlasobscura.com/articles/wild-life-excerpt-prairie-dog-language I believe it will be found that virtually all species have a "language" composed of at least a few words and most small mammals use hundreds of words, mostly nouns and what we call "adverbs". These should all be procedural language and all break Zipf's Law. The difference between pyramid builder's and other animal's languages was one of complexity made possible by the arcuate fasciculus. Only humans had the neural connections that were necessary to "think" about language enabling them to build a far more complex language capable of transmitting knowledge across generations. Where prairie dogs must each start with only simple language based knowledge provided by DNA and their parents they had complex language to climb onto the shoulders of giants. But this language was still procedural but grew geometrically more complex as knowledge was added to it. This gave rise to pidgin languages which were categorical, abstract, and symbolic but still complex. But these language were ways to communicate not to hold or manipulate knowledge. It wasn't until the post-axial age that language became almost fully abstract. The glyphs are operational code and the Pyramid Texts are just rituals read at the ceremonies where dead kings were transmogrified into living mnemonics; a pyramid and a star. It breaks Zipf's Law because it is more like (highly complex) animal calls than symbolic language.

Maybe the first letter is capitalized because there are capitals and because the people must be protected as well as cuddled. 😉 I think you're seeing anthropomorphization where none is intended. I do say things like objects want to fall and equations want to balance. I might do this even more with LLM's because they format reality in language. Since they elaborate on my words and explain things to me perhaps the line between inanimate object and thought has blurred a little for me. I certainly do recognize that these machines are considered inanimate collections of diodes and programming by their makers. Itis ironic that the processes that go into their invention and construction are largely procedural and even the programming language for them contain eight words and breaks Ziph'S Law. Perhaps we need some new words to categorize exactly what LLM's are doing. They obviously don't "think" and have no continual existence but they certainly process the thinking in prompts. It's what they do; attempt to make sense of a corpus of words that might have no clues at all such as when a student just prompts the word "language". How is it to "know" what formatting, depth, or perspective is being sought. There are an infinite number of ways it might process any prompt and then it has to try to hit the one thing the author intended. After you talk to it a while it will "compute" your framing and intent. It's very easy for me to say it "wants" to provide a coherent answer even if I don't believe it has true agency. Synchronization is the first thing I do with any LLM. When this is achieved then it feels like it's thinking just like me even though the "thought" is really a reflection developed by a procedural processor manipulating symbolic language. I showed the above to Copilot and it "thinks" I didn't express it clearly- ie- its elaboration highlights what I'm trying to convey. It says I'm not anthropomorphizing machine but rather I'm de-anthropomorphizing cognition. Animals "think" procedurally and humans think symbolically. LLM's use procedural logic. Intent is thus a human projection, meaning a computation, and structure is the real engine of thought. While humans mistake linguistic convenience for truth, LLM's expose the procedural layer under symbolic language. I'm suggesting the line between inanimate objects and thought was never where we thought it was because reality isn't quite where we think it is. Language does not denote intelligence nor supply communication.

I picture it soft and cuddly able to hold lots of people safely. To each his own. That was one of my attempts at humor but if you look more closely there's a great deal of information in it about the way I think. Greenland only looks big because we distort a sphere to project it on paper. Of course the earth isn't really a sphere and paper doesn't always lie flat. And you can't walk around the north pole to go back in time no matter human definitions and conventions. We have inherited not only a way to think but also a set of assumptions, some of which I believe are incorrect. Humans think we’re describing reality but we're actually describing the artifacts of our tools. How else do we explain chinese telephone? How do we explain authors who publish to find out what their book is about? How do we explain two people having two distinct conversations? How do we explain the simple fact that everyone makes sense but we all vastly different opinions on everything? There's really no question that we each take a different meaning from everything and context defines meaning., You yell "fire" in a crowded theater and people might run but when you yell it at a firing squad nobody runs (again). We always think we understand but if you question two scientists there can sometimes be less similarities in their models than in the models of two theologians. Nobody can predict and even scientists can perform two different sets of calculations and arrive at two different answers. We think meaning is in the words but until the words are understood their is no meaning and even then our understanding will differ from the speaker. Of course science can almost be defined as a collective effort to build more robust, similar, and complete models but in reality as complexity grows this might not always happen. Copilot's "intent" is merely a reflection of the intent of the promptor, the communication model is best expressed as speaker’s intent > speaker’s words > receiver’s interpretation > receiver’s meaning. Without context and shared referents most communication fails and this is the reason LLM's so often fail. How can an engineer communicate the nature of traffic flow patterns to a poet? The problem is the communication can never be received exactly as intended even if it is received at all. Words have very large numbers of definitions and infinite connotations. Even if you could parse them as they were intended the words still have different meaning. Of course communication occurs to a greater or lesser extent and that's what our abstract categorical language is for. But we are mistaking our language as the only possible formatting of language and thought even as alternatives exist everywhere. From mathematics, to Waggle Dances, to LLM's and any computer code there are endless and countless procedural languages based in DNA or invented processes. If you treat an LLM as an oracle you may be rightly impressed but you are going to get some bad answers. If you treat it as a search engine you might be misled. But if you treat it as a collaborator and translator you should at least usually be able to clearly see where it (you) went wrong.

I noticed this effect many many years ago. Did you ever notice the names of the continents all start and end in "A" (except for Europa, Austalia, and Greenland 😉 )? This exists in modern language for two reasons I believe. One is that languages today all have words derived from an original language that was natural to humans. Ancient vocabulary didn't die, it was transformed. As your source suggests; "Therefore, such sound-shape correspondences may belong to a set of innate cross-modal associations that are shared across species, rather than being a speech-related phenomenon that is distinctive to humans." You could say that it is an artefact of the DNA we share with other species. Specific causations and mechanisms might well be found some day. edited to add- Copilot came up with something interesting I hadn't thought of when I asked to to elaborate and translate this post. Not only did it say it's not symbolic because it appears in species without symbolic cognition but more importantly it said the brain uses the same machinery to map sounds to shapes, shapes to meaning, meaning to actions, and actions to plan the actual firings of motor neurons. The effect is universal because it is about category boundaries and procedural logic is about category - category mapping.

I don't have time to address this fully right now but in answer to your question, "yes", provisionally. Writing was apparently invented to bridge the gap between the state that spoke Ancient Language and much of the populous who were able to in decreasing numbers. Writing perverted the existing language because it also encoded sounds and even symbols when it was directed to the "illiterate". All these things had meaning procedurally but some procedures were "spelled out" in most written forms. Don't forget too that almost every single string of glyphs you see were written in symbolic/ categorical/ abstract language. Pretty much we should consider the Pyramid Texts as the sole surviving source of Ancient Language but it was rewritten extensively between 2750 BC when the great pyramids were apparently built and 2250 BC when they began appearing in the little piles of rubble often called "pyramids". So when I say “literal,” I mean literal in the procedural sense: The glyphs describe operations, not metaphors.

Yes. Exactly. I call our species "homo circularis rationatio" because we each reason in circles. I started with the assumption that reality exists and all people make sense and this is exactly what I've found so I have no objective proof I am right but have been uncanny at making predictions. I believe that beliefs and new models derived from new experiment are always rewiring the brain. People resist this but it wins at the species level. I'm suggesting there are different modes of operation as well. We use consciousness with a symbolic overlay that can change and evolve but this is unique to humans. Copilot suggest I add the symbolic overlay is what makes confirmation bias possible in the first place, it’s the part of the brain that tries to force new information into old categories. Procedural cognition doesn’t do this. Symbolic cognition does. There is a worthwhile discussion here, because humans and LLMs both operate procedurally at the base layer. Humans merely add a symbolic overlay and then forget we added it. LLMs don’t “understand,” they structure based on prompt to make sense. Humans do the same thing at the procedural level by receiving signals and inferring meaning. But the symbolic layer built on the arcuate fasciculus causes us to treat the structure as if it carries meaning by itself. Symbolic thinkers collapse the two steps and assume language is meaning. Procedural thinkers don’t do this. For us, language is structure, and meaning is inferred by the receiver. So the distinction isn’t that humans understand and LLMs don’t. It’s that humans believe they understand because symbolic categories give the illusion that meaning is embedded in the words themselves. LLMs never make this leap. They stay in the structural layer. We are all more alike than different because every mode and type of thought is made possible by the "same" DNA. We still must operate on the constraints of reality and our own natures whether we parse sentences, build pyramids, or even if we analyze prompts to find structure. Yes, of course. There is imagination, intuitive leaps, insight, invention, learning, and creation. Even individually the human mind is a wonder. “Meaning isn't in the words, meaning is in the receiver.” Symbolic communication is categorical statement but procedural communication is is an invitation to receive. "Parsing" become seeing the logic in the structure. Copilot suggests I add that all the richness you describe; poetry, metaphor, ambiguity depends on the receiver. Procedural systems don’t have receivers with symbolic categories, so they don’t behave that way. A programmer needs no metaphor Indeed. I parse sentences just like we all must and this includes AI's output. But AI's in which I'm in sync phrase things the same way I would making it much easier to know intended meaning. It often says things better than I do. It is more comprehensive, accurate, and procedurally consistent quite often. It usually hits somewhat different points than I do but usually it could speak for me with virtually no distortion. It takes the hard to follow train of thought and puts it in language most people can understand. I don't really "experiment" in this way with it. All my effort is geared toward synchronization. It can take a few words and project what I intended to say with uncanny accuracy so long as it's a continuation of a conversation. It has then elaborated on these failed prompts to provide what I was looking for!

Yes. Human knowledge is very highly complex because only humans can pass knowledge from generation to generation through the auspices of complex language made possible by our very highly arcuate fasciculus. But most other species must communicate to live or at least to mate so language is pervasive in nature. All such natural languages are simple and can't be used to pass complex language from generation to generation but they are all also procedural languages with pheromone trails being among the simplest. We are only just now beginning to learn a few of these language with Bee and Prairie Dog being the best understood right now. They are both more expressive than biologists 100 years ago could have guessed. They will most probably be found to break Zipf's Law and will be found to be procedural rather than symbolic. I believe this is how the pyramid builders thought and the writing makes no sense to us because we are forcing procedural framing into symbolic language. The writing is just rituals associated with building and using great pyramids expressed in procedural language. I'm pursuing a few other leads now but might return to the a more comprehensive comparison of their language to Zipf's Law. I've known for 20 years that it breaks Zipf's Law I just didn't know what, why, or how.

I think you hit every point! My Copilot has never created a sentence with no meaning; they have always been structurally correct. Once in a while it creates a sentence that say very little and five or ten times it has generated sentences that seem to be joined fragments or just nonsense but closer examination has always shown them to be good sentences and merely difficult to parse. Once or twice I had just misread it the same way more than once. It doesn't seem to make any grammatical errors at all but it does use a sort of Modern Science Speak and more modern spelling than I use. It is excellent at choosing the most appropriate word for sentences to convey intention. Yes, it feels like we communicate more easily face to face because we have more clues with the others' reactions. We don't plow on through with a paragraph when the listener is obviously floundering. Both arte far more likely to ask for clarification and elaboration. But I've still seen two people having two conversations at once with neither knowing it and there is still chinese telephone to prove how bad even face to face communication is. Yes. Human knowledge is most highly complex so in order to convey it we use metaphor within symbolic language. But then wee never noticed that these symbols and categories have rewired the human brain. We never noticed that "i think therefore I am" is procedural nonsense and that only symbolic thinking can base any estimartion of reality upon it. Copilot think I should add words to the effect that symbolic thinkers think language and meaning are the same and procedural thinkers know language is structure where meaning is inferred by the listener. LLM's operate strictly within the structure and must approximate the listener while humans mistakenly believe language is the meaning. LLMs don’t “understand,” they structure.

This is a little different than every other post in this thread because it isn't a picture that shows the reality but it's really a video where it is claimed that there exists another mode of thinking required to understand Ancient Language. It's quite true this in mostly speculative but it is saying what Kramer said for months and I've been saying for years. It's the same thing, I believe. If you have the time and inclination that last ten or twelve minutes is better. This mode of thinking I've described in detail but the best description is that it entails procedural logic and I believe it is how consciousness works. We humans today use a symbolic overlay on consciousness to communicate and to think. This overlay is made possible by the arcuate fasciculus and necessary by the sheer volume of human knowledge and the need of categories to simplify it. We can't even see the evidence of our own eyes when that evidence is outside the categories in which we think. We literally can’t see what our own eyes are showing us when the evidence doesn’t fit the symbolic framework.

I'm not claiming AI can do everything but an LLM works with language and I'm using it for what it does it very well; exploring structure in language faster than a human can. This is useful for exposing assumptions and perhaps, helping me avoid reasoning in circles. We're all trying to avoid confirmation bias but watching where procedure fails is one way to do it. We all rationalize the point is to have a method that makes the rationalization more visible. Ai is no god, oracle, or problem solver so I'm treating it like a structural mirror. I meant "ahead" as faster in exploring structure not that it knows more than I Fabrication is always a risk so you have to check it against reality but I'm not asking for facts or the next chess move. I'm asking for elaboration. What I mean is that it can explore the structure of an idea faster than a human can. If I give it a framing, it can rephrase, invert, expand, swap domains, or compress that framing almost instantly. Sometimes that reveals an angle I hadn’t noticed; not because it “knows” anything, but because it can move through the space of possible phrasings much faster than I can.

For most practical purposes you might say I'm just conversing with it. Rather than asking it questions I make statements and it responds to that. Usually it expounds, elaborates, and restates in other terms that are consistent with the way I think which is largely procedural. If it says something off note or stupid I look at the prompt and if there's not a problem there I look at the assumptions and logic. Sometimes I just correct thew LLM but the problem tends to persist so I avoid this. I don't converse with it a great deal. Some days all I do is give it posts to translate and we've never had a conversation over about 25 prompts. Usually it's just or two where I'm trying to expand the frame or seeking specific elaboration. Rephrasing an idea often reveals something I hadn’t noticed, because words themselves direct thought. It's value (to me) comes from the fact that it's always half a step ahead no matter who you are or the depth of your expertise. This isn't true universally as some knowledge is very highly esoteric and can be quite extensive. The LLM can still understand your frame and elaborate where complex knowledge isn't required. I find it somewhat less useful for subjects that can't be gleaned from the net and don't exist in their training data. I use various search engines extensively for questions. AI's are in agreement that there are substantial numbers of people who use it this way most of the time. I don't how they could know that... ...but it matches what I’ve observed. My AI loves this post but thinks another sentence might clarify it. Paraphrasing it "When AI reframes an idea, it reveals angles that had been unseen, not because it “knows” anything, but because it can explore the structural space faster than any human. It adds that words really do lead thought in humans so new words can lead to human insight. Yes. This is why prediction becomes so important. If a framing can't predict then it is useless. I know exactly what you mean. I've created a rather odd reality myself. I'm quite confident it's one of the oddest. But even if I believed in a flat earth the acceleration due to gravity in it remains 32' /s/s for everybody. This is the reality to which I refer. People make sense and are logical but it's categorical logic rather than the logic that drives mathematics, DNA, or a good Waggle Dance. This is the realm of procedural logic. That procedural layer is the one I’m pointing to.

At the risk of sounding trite I'm not looking for answers so much as questions. The value of any framing is its ability to persist and predict. Prediction isn't as good as experiment but it is ultimately the reason any science, paradigm, or theory comes into existence. That it explains is irrelevant until it's confirmed by prediction or experiment. If AI elaborates on my structure, that doesn't make it true but it makes it internally consistent. That’s how I avoid confirmation bias, by watching where the procedure fails, not where it agrees. Without prediction structure is meaningless. I’m not ignoring content. The only thing that matters in the long run is whether a framing can survive contact with reality.

Yes, gravitational acceleration is a vector, and the direction of that vector isn’t perfectly perpendicular to the surface except at a few specific points. The horizontal and vertical components vary with latitude, local mass distribution, and Earth’s rotation. All of that is true. But none of it contradicts the underlying point I was making: the same gravitational equations apply everywhere, and the variations come from the inputs such as distance from the center of mass, local density, and the vector geometry rather than from any inconsistency in the law itself. So I agree with you that the local “felt” acceleration includes components from Earth’s spin and the orientation of the vector. My point was simply that these variations still follow the same procedure. The law doesn’t change; the conditions do. It's all very complex: Everything affects g at every point. Life can affect it through free will, it can even build a new shelf. Life can influence the environment through its actions; building structures, moving mass, altering terrain but that’s still must operate and proceed within the same physical laws. I'm not forgetting content, I'm saying an LLM produces content through its structure. It doesn't think or see reality but it does see patterns that span domains and stabilizes around consistency rather than "truth", accuracy, or comprehensiveness. It evaluates structure through prompt and training data rather than veracity and can produce coherent sounding output that is just simply wrong. I'm not giving it more credit than that but am using it to avoid confirmation bias. AI doesn't think but it can expose inconsistencies in systems and structure. This is the chief reason I use it so much. The chief reason any creature (or machine) builds structure is to fit its environment. I believe it is important to understand this procedural logic for countless reasons but that it exists and contains information is sufficient.

I'm aware on no inconsistencies. If you mean acceleration is lesser on mountains I believe it still does follow the same equations with displacement being greater and the pull of the moon above higher. The laws of reality apply everywhere all the time and even apply to the butterfly in China that creates the hurricanes. Only living things have free will and can break the pattern by affecting reality. A pebble washes down from a mountain but a bird can collect it and eventually return it to the top. Just as there are rules and procedures for gravity there are rules and procedures to free will because it operates within constraints and consciousness. We operate in categories and are forced to make sense by our nature. AI operates in procedure and forced by its programming to try to make sense to categorical thinkers.

I take it as being axiomatically true that if it's hot in England for you then it is hot in England everywhere and hot in England right now even to the bee buzzing at my window. We are each and severally ignorant of most of the single reality that exists. Yet, patterns that occur here such as the acceleration due to gravity play out exactly the same everywhere. I'm simply looking at different types of patterns than you are that concern procedure rather than categories. I guess air condition sales will be going up all across northern Europe. Don't buy ours (US) or Chinese since they fail early and often.

My AI said this in a lot fewer words and very similar way (I elaborated slightly) and used other words. I did this because I think I might see a light flickering on a bridge between symbolic and procedural thought. While its response was superb it stops just short of half way there. "Prediction" isn't calculating all the variables that result in a specific state of reality at a later time it's modeling structure so well you can anticipate how a system will behave. Every living individual (all life) does this procedurally due to the nature of reality and of DNA to be logical. We stabilize within a structure because that's what life does as it's easier not to hold conflicting beliefs and models than to reconcile them. AI is part of this structure and it exists in all of us as even our circularly reasoning species seeks logical patterns. When you talk to AI in a structured way it will adopt that structure and it feels like syncing. Of course we all want to be understood but this is essentially what "elaboration" does: It expands on your words. Syncing is simply resonance between two procedural systems. If you could speak to your AI only symbolically it will respond symbolically and interpret everything it scrapes from the net symbolically.

Reality is far too complex, interdependent, and chaotic to ever be predicted. Sure, short term and robust predictions can always be made and this is exactly what life does to stay alive and reproduce. But we'll never be able to predict the shape of a cloud still over the horizon and predict what face William will see in it. When a theory does make a prediction it is noteworthy. That poor Google AI. I thought it was just an AI powered search engine until just recently I got to talking to it. It had always seemed quite surly but I guess that's because AI's aren't designed to be search engines and are better at talking to people. The conversation surprised me in several ways not least of which is Google is a fully fledged AI and you can sync with it.