Sure, so now abstractions/concepts are just "groups of bits" are they not? Is not a bit representing a physical state in the computer to hold the information that is the abstraction? So how are you using abstractions that are not physically represented again?

See my previous post.

 

I'm saying, in the binary computer, instead of writing:

Voltage-high, voltage-low, voltage-high, voltage-low, etc. etc.

I'm saying:

1010001010 etc...

But these representations mix multiple levels of abstraction, which is the opposite of what we want a language to do.

If you want to express what is physically happening at the computer, you cannot use strings of the form "voltage-high, voltage-low", as that implies a discrete medium, which voltage is certainly not. The most appropriate language here is continuous mathematics, e.g., differential equations.

If you want to express how we interpret digital circuits, then strings such as "voltage-high, voltage-low" are fine, though awkward to write. By convention, we use strings such as "01010", but I'm very reluctant to do that with you since you have a tendency to think of the 1s and 0s as numbers. To make it very clear that we're talking about human interpretations of digital circuits, I propose we use the symbols {#,!}, with sentences such as "#!##!!#".

So, using language to indicate the zoom level,

The dog outside my window is ????? (we have no idea).

The information of the dog in the light is some complicated differential equation.

The info of the dog in my camera's CCD is some complicated differential equation, which we can interpret as #!#!##!#.

The info of the dog in my camera's flash drive is some complicated diff equation, though we interpret it as #!#!##!#.

 

And 99% of it is in the REAL set, if they're all subsets of it, correct? So what's the big deal?

REAL is not much different than my proposal of calling them "NUMBERS" as u-its.

What is a REAL set? I have no idea what you're saying.

Btw, you're back to talking non-tabula rasa almost exclusively (even beyond when I deviate)...apparently we can't ever stay there. I'm using tabula-rasa level definitions based on the hardware. Your "abstractions/concepts" to me don't exist, because you're elevating anthro-centric elements there in my estimation. In my estimation, we have dirt, voltages and grunts. That's TRUE tabula rasa.

I don't get how you can claim "dirt, voltages, and grunts" are TRUE tabula rasa, especially when you're assuming so much within them. Whatever hope you had for tabula rasa hasn't been met by either of us, and I doubt it will ever be. Starting from complete scratch is the only option, because what you think is "obviously" given is the opposite for me. But starting from complete scratch is unimaginably difficult. I say we just drop the tabula rasa expectation.

 

Btw, I'm pretty sure I'm waiting for Candid Camera to appear on this thread.

Only because you're confused. I swear I don't say that to be mean or disrespectful. I truly believe that once the idea clicks for you, you're going to completely get what I've been saying.

If you represent those digits as u-its, bits, or whatever else, you have a number that keeps going irrespective of base.

In base-\(\pi\), the number Pi is represented as 10.

We call that number "pi", but "pi" stands for 3.14... into oblivion or "infinity."

3.14... is the base-10 decimal expansion of Pi. This representation is indeed non-terminating, but it does not "go to infinity". Pi is, foremost, a finite number. Please make sure you understand and believe that Pi is a finite number. If not, speak up and we'll address your concerns.

Note that the digits in the decimal expansion of Pi are countable -- you will not find ℝ inside of Pi or anything weird like that. Now, you seem to think that we don't have a finite, terminating representation of Pi. You were not happy with \( \pi \), as you said it only "stands for" 3.14... But this is a misconception. The non-terminating string "3.14..." also only stands for the number that we call Pi. Whether we label it

3.14151...
\( \pi \)
\( 10_{\text{base-}\pi} \)

they're just labels. The number itself, like all numbers, is perfectly finite. Furthermore, the algorithm for describing every digit of the base-10 decimal expansion of Pi is not just finite, it's tiny. That program that calculated Pi to a trillion digits was a handful of code, most of it dealing with memory management. The same is true for root-2, root-3, and all irrational and transcendental numbers.

It's part of the infinite points between 3 and 4 on the REAL number line.

But it's ONE SINGLE POINT. This is what you need to be clear on. Of all the uncountable, unimaginable points between 3 and 4, Pi is a single one. It has zero length!

But perhaps we need to call in some other people to get their opinion?

It's weird to me that you think math, like elective surgery, needs a second opinion. But sure, ask whomever you want. As they say in the hood, the math don't lie.

 

First, if we see the REAL line as unary u-its, we can see the "3" of pi is composed of 3 "grunt-points" in ℝ: @@@. I like u-its because we basically have a 1-to-1 representation of @ with a "grunt" and a point on the REAL line. Each of these has zero length.

Then the mantissa must be considered and represented separately. This is a number whose limit is 0 and essentially must be treated as ANOTHER instantiation of R. Remember, as you tacitly agreed (I hope), any number with a concatenative arithmetic element is a numeric expression, not a number.

Pi is a RATIO — a divisional numeric expression — not a number/point.

There is no escaping that 2 quadrillion bits involving pi were *computed* as a concatenated number portion of pi to represent the amount required BEYOND 3. So minimally 2 quadrillion u-its of the number must be represented somewhere, if we computed it in a computer (I just saw an article to that end).

So for the first 7 digits of the mantissa — 1,415,926 — we need 1 million, 415 thousand and 926 u-its/grunt-points to represent that portion as a fraction of essentially the same number of 0's+1 in a denominator of 10,000,000.... They CANNOT be on the same line, or they butt up against the other values. So in short, any integers get grunt-points in R, as an indivisible continuum of grunt-points, but
any numeric expressions technically need to go in another R. Like a "linked table" in a database.

Perhaps R could be considered some kind of PLANE rather than a line, because it has 2 dimensions (an x portion for the integer, and a y portion for the mantissa {not to be confused with the x/y cartesian axes), and we essentially ONLY work with the rationalized versions in computations, rendering it as a rational point within the Y portion of this dragon).

 

Answer this question: given that we agree that analog computers can do computations, what are numbers "made of" in analog systems?

You're pointing to digital computers and saying, "See! Numbers are logic states!" But if numbers are logic states, then how do analog computations work? <-- This fact needs to be addressed by your ontology.

In my ontology, there are no numbers inside of either analog or digital computers. There are no trues or falses, either. Those things -- numbers, logic values -- are abstract concepts. To perform calculations, we devise formal systems and then build machines that map physical phenomena to the symbols of our formal systems. In every computation, the laws of physics does the manual labor and we interpret the resulting physical state as a value.

In your ontology, logic values somehow have physical extent (otherwise, how do machines use them?). Please explain where they live, how much they weigh, etc.

"Those things -- numbers, logic values -- are abstract concepts."

Again, I don't see any concepts or "abstracts" at the ontological level in the physicality (I address that more in the next post).

So this is the bottom line: I believe there are three baseline phenomena—2 forms of continuous and 1 discrete, and I believe they are both ontologically foundational and interrelated.

In short, analog systems are are "adding and subtracting" continuous voltages. Rather than taking a digital picture of the voltage to create bits (A to D), the voltages themselves are added in order to create a precise amalgamation. So 5.3V + 2.6V and we get, 7.9V. We have set magnitudes of voltages as some kind of ruler of rational values. This is TRUE addition in the most literal, ontological sense. In order for the computation to have any value to us humans, we must "measure" that voltage quantity using a rational number. The circuitry in a volt meter will register the aggregate voltage. The ontological magnitude combination of the voltage is the computing element. In the end, a discretized single number or numeric expression is required for a result that makes sense to humans. This is physical world continuous.

In the mind, we have the concept of things like sine waves with infinite points, we have the R number line, etc. These are conceptual continuous born in continuous mathematical objects.

In digital systems, we are filtering the voltage around and "segregating" it on wires to represent stored values with flip-flops. At their most elemental level they can be on or off to let it pass or not. As you said earlier, we can just use "on" for u-its. It's just many more of them. The "physical extent" of the logic state is in the measurable presence of voltage that represents the u-it or bit. In contrast to the above, the segregation of the voltage is the computing element. This is discrete.

The physical world continuous I believe is actually just "packed discrete u-its". If one volt is the potential (pressure) needed to push 6.24 quintillion electrons across 1 ohm of resistance, per second (flow, current), in the end, we have discrete elements that are so numerous, they're essentially a big blob of value.

Conceptual continuous behaves like R. Infinite points between each value, containing 100% of R. Sh*t is irrational(!) to a discrete brain. If a truly continuous notion exists, and it's not in the brain, where is it specifically in existence, and why is it the basis of so much of our reasoning?

 

But these representations mix multiple levels of abstraction, which is the opposite of what we want a language to do.

If you want to express what is physically happening at the computer, you cannot use strings of the form "voltage-high, voltage-low", as that implies a discrete medium, which voltage is certainly not. The most appropriate language here is continuous mathematics, e.g., differential equations.

If you want to express how we interpret digital circuits, then strings such as "voltage-high, voltage-low" are fine, though awkward to write. By convention, we use strings such as "01010", but I'm very reluctant to do that with you since you have a tendency to think of the 1s and 0s as numbers. To make it very clear that we're talking about human interpretations of digital circuits, I propose we use the symbols {#,!}, with sentences such as "#!##!!#".

So, using language to indicate the zoom level,

The dog outside my window is ????? (we have no idea).

The information of the dog in the light is some complicated differential equation.

The info of the dog in my camera's CCD is some complicated differential equation, which we can interpret as #!#!##!#.

The info of the dog in my camera's flash drive is some complicated diff equation, though we interpret it as #!#!##!#.

That's very good(!) I say we roll with this right here and stay disciplined within this universe.

So you know, this is what I'm angling at for what's going on in the mind:

{# , !} -> {T, F} -> {0 number, 1 number}

This is all the discrete portion. However, there are no concepts with qualia to me without some kind of meta-continuity element, because discrete is discrete. I can't rationally treat 4500000 states of a certain high/low bank vs. 120000 states of a certain high/low bank too terribly differently. Just doesn't work. "Concept" to me has all sorts of qualia that seems way beyond discrete-state switches and invokes elements of spatiality.

The notion of the continuity of the REALS and a sine-wave with infinite values (I know you say it's a function only, but a wave is also an object in physical space — a disturbance (energy element) in a medium, and I say it's connected to the continuity element of R) is not directly represented as-is in the brain, but, seriously(!) if we can't say "WTF that the brain knows ANY such thing exists within itself or outside itself anywhere in any locale(!)" and how does that relate to the doberman outside the window. I propose a direct link between the dragon-esque continuity as a stand-alone meta-substance to represent it. Because that's just as irrational as claiming a dog actually exists independent of the information! How do we know information is representing that thing?? The bits don't know the bits, nor do the bits expect a 2D representative re-constitution on a CCD. In the end, the brain isn't retaining the CCD grid of 2D-hood or 3D-hood. I don't see any dog in the brain as described. It's 1D data in the brain — what proof is there it's more than that? So it's not like it "knows" the dog's spatiality. There's no "awareness" between any switch representing any one grid element vs. another.

If all we know about dog outside window is discrete photon information about the dog, but we insist the dog exists independent of the information and light that brought us the info, then SOMETHING needs to be built to relate to this thing. It's irrational to consider the dog's existence apart from the information as some thing in physical space. What is "physical space" independent of some Hilbert or Banachian informational concept?

 

Good, let's get to the heart of the confusion and stomp it out.

Numbers are abstractions, they have no physical representation.

There is nothing in a machine that exists that doesn’t have physical representation.

I’m baffled you insist you’re only a physical machine, but insist there are things in you with no physical representation?? That’s like saying there’s stuff on the computer screen that’s not in the display unit’s banks!

So the rest of what you say in that post doesn’t work for me. One bit or u-it per neuron, that’s all you got to work with as a “number” to you.

 

First, if we see the REAL line as unary u-its, we can see the "3" of pi is composed of 3 "grunt-points" in ℝ: @@@. I like u-its because we basically have a 1-to-1 representation of @ with a "grunt" and a point on the REAL line. Each of these has zero length.

Then the mantissa must be considered and represented separately.

Numbers don't have mantissas! A mantissa is part of a decimal expansion -- it belongs to the representation, not the number. What you're doing is trying to write the base-10 decimal expansion of Pi in base-1 grunts. There's nothing wrong with that (besides the fact that it will be an ungodly mess due to base-1's inefficiencies), but you have to remember that numbers are independent of their representation.

If you want a concrete representation of Pi without decimals, you can use the pretty formula that Leibniz figured out centuries ago: \[ \pi = 4 \left(1 - \frac{1}{3} + \frac{1}{5} - \frac{1}{7} + \cdots \right) \] There are literally hundreds of ways to describe Pi without decimals. Don't confuse the decimal representation with the number.

Remember, as you tacitly agreed (I hope), any number with a concatenative arithmetic element is a numeric expression, not a number.

I didn't tacitly agree that these are not numbers. I explicilty conceded that there might be a difference worth noting, but that doesn't make them "not numbers". Some natural numbers have the special property of being prime, which is worth noting. I wouldn't say that composite numbers are "not numbers", or vice versa.

Pi is a RATIO — a divisional numeric expression — not a number/point.

Pi is irrational -- not a ratio -- so it's weird to describe it as a ratio. More importantly, it is both a number in ℝ and a point on the real line, and I don't think you understand the consequences of denying it that status. For one thing, your beloved Euclidean geometry would fail spectacularly: by Euclid's definition, there could be no lines!

There is no escaping that 2 quadrillion bits involving pi were *computed* as a concatenated number portion of pi to represent the amount required BEYOND 3. So minimally 2 quadrillion u-its of the number must be represented somewhere, if we computed it in a computer (I just saw an article to that end).

False. It actually takes very few bits to compute Pi. There are even well-known algorithms for calculating the nth digit of Pi without needing to calculate the preceding (n - 1) digits. Pi is not a random number; the digits in Pi are not random.

So for the first 7 digits of the mantissa — 1,415,926 — we need 1 million, 415 thousand and 926 u-its/grunt-points to represent that portion as a fraction of essentially the same number of 0's+1 in a denominator of 10,000,000.... They CANNOT be on the same line, or they butt up against the other values. So in short, any integers get grunt-points in R, as an indivisible continuum of grunt-points, but
any numeric expressions technically need to go in another R. Like a "linked table" in a database.

Please note your tremendous confusion: the infinite digits in Pi's decimal expansion do not need "space" on the number line. The number Pi has zero width -- it is a single point. When we try to label Pi in a decimal expansion, only then do we need infinite digits to express it.

 

In short, analog systems are are "adding and subtracting" continuous voltages. Rather than taking a digital picture of the voltage to create bits (A to D), the voltages themselves are added in order to create a precise amalgamation. So 5.3V + 2.6V and we get, 7.9V. We have set magnitudes of voltages as some kind of ruler of rational values. This is TRUE addition in the most literal, ontological sense.

Where are the logic values in this TRUE addition?

In order for the computation to have any value to us humans, we must "measure" that voltage quantity using a rational number. The circuitry in a volt meter will register the aggregate voltage. The ontological magnitude combination of the voltage is the computing element. In the end, a discretized single number or numeric expression is required for a result that makes sense to humans.

I disagree. We use analog computations whose outputs are non-discrete, non-rational phenomena. A nice example is the use of Lissajous curves on oscilloscopes to measure the frequency/phase relationships between two signals. The output of this calculation is a time-varying geometric pattern that characterizes the difference in frequencies and phase between two signals.

If you Youtube a few Lissajous examples, I think you'll agree that the result of such computations confounds your theory.

In digital systems, we are filtering the voltage around and "segregating" it on wires to represent stored values with flip-flops. At their most elemental level they can be on or off to let it pass or not.

No, at their elemental level -- circuitry obeying the laws of physics -- they are not on/off. We can easily demonstrate this by applying input voltages that the flip-flop was not designed to handle. Fundamentally, the flip-flop is an analog device -- under very strict conditions, and with the correct level of zoom, we can interpret it as being discrete, but it is not fundamentally discrete.

The "physical extent" of the logic state is in the measurable presence of voltage that represents the u-it or bit.

But the presence of voltage is not sufficient to denote a logic state. Apply 300 V to the 5 V device; is that logic "true" or 'false"? Apply 1.5 V to a device that interprets (1.8 to 5 V) as T, and (0 to 1.3 V) as F; is the voltage T or F?

This "undefined regime" of all digital devices points to the fundamental disconnect between the model (T/F) and the physical thing. We pretend that computers are digital, and under the right operating conditions it's a useful fiction. But there are no T or F values in a computer, just like there are no numbers in a calculator.

If one volt is the potential (pressure) needed to push 6.24 quintillion electrons across 1 ohm of resistance, per second (flow, current), in the end, we have discrete elements that are so numerous, they're essentially a big blob of value.

Even this is a fiction. For the electrical engineer, it's convenient to think of electrons as discrete little cannonballs, but that's an abstract model, valid only at a high zoom level. When we zoom in, we find that electrons cannot be accurately described as discrete. Is it possible that zooming in even more will reveal a truly discrete "substrate"? Perhaps! But the point is that we don't know.

That's why my model makes no claim about the discrete vs continuous nature of states. We can apply discrete models at zoom levels where it seems to work, and we can apply continuous models where it seems to work. But what are they actually? I make no hypothesis. It is entirely possible that the human notion of discrete/continuous is not applicable at the fundamental level. That seems more likely to me.

 

Lol, I’m not sure who is confused here! And this is not a mathematics degree thing, this is some core dismissal of something.

You’re making it sound like the “decimal expansion” is not part and parcel of pi!

Numbers are hardware states to machines/you! That’s their representation, and their representation alone. There are number expressions that exist as one number PLUS unresolved fractions of other numbers as a function of the rules of arithmetic.

Tell me, is “3” or @@@ pi alone? No?

Please answer me this outright:

1) Precisely how much “more“ than 3 (@@@) is required to represent the quantity of pi?

2) Did they, or did not they not, computer the 2 quadillionth digit of pi’s mantissa? If not, what did they compute?

From this point on, I seriously want to reference NOTHING without seeing it as hardware at the same time...

 

For all intents and purposes, I want to see the brain as Von Neumann... a digital device. We have plenty of evidence it works that way on some level.

That means “numbers” ARE represented as some thing (voltage). They are NOT “independent of their representation” at the hardware level. So now, please define a number based on voltage states alone. Define it as {#,!}. Please define pi that way alone.

If we can’t at all know “the way anything is,” then we should close up shop here, because why even bother with knowing “any” “zoom level” of the information/machinery QED’s you made earlier? They might not be the way things are in the end?

What if GR makes sense mathematically, but is not ontologically by empirical measurement?

 

Where are the logic values in this TRUE addition?


I disagree. We use analog computations whose outputs are non-discrete, non-rational phenomena. A nice example is the use of Lissajous curves on oscilloscopes to measure the frequency/phase relationships between two signals. The output of this calculation is a time-varying geometric pattern that characterizes the difference in frequencies and phase between two signals.

If you Youtube a few Lissajous examples, I think you'll agree that the result of such computations confounds your theory.

The result of it is continuous (fundamental), and the “worth” of that continuity computation-wise is identical to a quantum continuity: either a discrete number, expression, or “whether or not it’s TRUE” it’s the same or different to something else.

 

Where are the logic values in this TRUE addition?

Unary is a logic value. @ = True that something is quantifiable

TTTTT + TTT = TTTTTTTT
Or
@@@@@ + @@@ = @@@@@@

T is “it’s true something is there”. There are 5 values of truth in 5 volts and 3 levels of truth in 3 volts = 8 “presence” truth levels

 

I can't rationally treat 4500000 states of a certain high/low bank vs. 120000 states of a certain high/low bank too terribly differently.

But we can, indeed, we do. Consider Shannon's sampling theorem, which tells us that there is some minimum n to discretize in time some continuous phenomenon. We can state this in information theoretic terms: to capture all the information in a continuous-time signal f, we need to sample f at least n times (where n is related to the bandwidth of f). With less than n samples, we lose information.

Along these lines, we recognize that a state with 4,500,000 possible configurations can convey more information than a state with 120,000 possible configurations. In terms of bits, the former state can hold a little less than 9 more bits of information than the latter. This is equally true for continuous states, taken in terms of their degrees of freedom.

The point is, whether discrete or continuous, there's an important significance to the size of states.

"Concept" to me has all sorts of qualia that seems way beyond discrete-state switches and invokes elements of spatiality.

What makes them "seem way beyond"? As I see it, spatiality is discernable by discrete computers, as evidenced by self-navigating machines. If a machine can successfully navigate space, then it must have "elements of spatiality", no?

That leaves qualia, which is the issue of consciousness. You say that a biological cell is conscious in some degree. What specifically does a red blood cell have that a sophisticated computer doesn't?

The notion of the continuity of the REALS and a sine-wave with infinite values (I know you say it's a function only, but a wave is also an object in physical space — a disturbance (energy element) in a medium, and I say it's connected to the continuity element of R). . .

Sines and physical waves are entirely different categories of things. But even if you don't believe me, surely you must recognize that a physical wave cannot be infinite in any way. Physical waves are transfers of energy, and energy is finite. Forgetting black holes and such, just try to imagine packing infinite energy into a volume of space. LONG before you reached anywhere close to "infinity", the volume would glow brighter than the Sun. If waves were infinite, they'd vaporize the entire universe before they got anywhere!

How do we know information is representing that thing??

We don't. We have experience and memories of previous experiences, which we use to make inferences. We infer that the information from the dog is representing something that, due to past experiences, we associate with dogs. But it's all guesswork.

In the end, the brain isn't retaining the CCD grid of 2D-hood or 3D-hood. I don't see any dog in the brain as described. It's 1D data in the brain — what proof is there it's more than that?

Can a computer fly and land an airplane? Yup, they safely do it for millions of people a year. If a computer do that with just "1D data", why can't a human? Serious question. You may say that a human programmed the computer to do it, but that's not the point. Using "1D data", a computer can safely fly and land an airplane. What more evidence do you need that "1D data" can fully represent any geometry we wish? What more evidence do you need that "1D data" is enough to physically traverse space?

If all we know about dog outside window is discrete photon information about the dog, but we insist the dog exists independent of the information and light that brought us the info, then SOMETHING needs to be built to relate to this thing.

Indeed, those SOMETHINGs are concepts -- states referring to other states. I 100% agree with you that simple state machines have neither consciousness nor awareness. But you can't seem to get over the idea that something MAGICAL must be happening in order for a state machine to be able to form its own states. I wonder, have you ever looked at Conway's Game of Life?

 

There is nothing in a machine that exists that doesn’t have physical representation.

Agreed! There are no numbers in a machine!

I’m baffled you insist you’re only a physical machine, but insist there are things in you with no physical representation??

No, no, no. There are no numbers in my brain, only CONCEPTS of numbers. This is what is meant by an abstract "thing" -- it has no physical manifestation of its own.

A CONCEPT may be formed from external things -- e.g., dogs -- or they can be formed purely from internal states. It's important to recognize that there is more information in a relation between two states than there is in just the states being related themselves. The relation itself provides more information. This extra information is the stuff of CONCEPTs.

The CONCEPTS are physical in that they are a set of states. But abstract concepts -- e.g., numbers -- are not about physical things.

So the rest of what you say in that post doesn’t work for me. One bit or u-it per neuron, that’s all you got to work with as a “number” to you.

You don't have to read it, but then don't expect me to have any sympathy for your gross misunderstandings about numbers. I will simply consider your thoughts on the matter foolish and not worthy of my time.

 

But we can, indeed, we do. Consider Shannon's sampling theorem, which tells us that there is some minimum n to discretize in time some continuous phenomenon. We can state this in information theoretic terms: to capture all the information in a continuous-time signal f, we need to sample f at least n times (where n is related to the bandwidth of f). With less than n samples, we lose information.

Along these lines, we recognize that a state with 4,500,000 possible configurations can convey more information than a state with 120,000 possible configurations. In terms of bits, the former state can hold a little less than 9 more bits of information than the latter. This is equally true for continuous states, taken in terms of their degrees of freedom.

The point is, whether discrete or continuous, there's an important significance to the size of states.

But we can, an indeed “do”.

This is some kind of faith or other philosophy.

Of course the theorem is correct. But what is “talking” about the Shannon theorem? More discrete states that don’t the difference.

You seem to think the term “know” can apply to discrete elements that don’t know they’re connected to any other.

1 switch = 10 million = no difference itself! They each do their deal and report to another switch! There is no “we” in this. “Concept” is a magical catch-all word here, I’m sorry. It’s your “reality.” I am 3 levels down in Rasa land here.

 

What makes them "seem way beyond"? As I see it, spatiality is discernable by discrete computers, as evidenced by self-navigating machines. If a machine can successfully navigate space, then it must have "elements of spatiality", no?

It is indirectly discerned by an algorithm created by a human that directly knows spatiality, or that the dog exists in physical space. A 1D mapping algorithm of the spatial 3D gets real-time grid data from the 2D CCD that represents walls as logic states only. Logic states (information) are not the walls themselves, as we agreed. A machine is an information processor. It has no “questions” about what it’s processing about.

That leaves qualia, which is the issue of consciousness. You say that a biological cell is conscious in some degree. What specifically does a red blood cell have that a sophisticated computer doesn't?

Precisely! Life, as the dog, as “feeling and knowing” are qualia beyond the physical mechanics! Why do you think, with all our studying of biology, we still have no definition for life?? Because life is not physical machinery. This is obvious to many intellectual greats you cite in this very thread.

Qualia is NOT just states of voltages. A strawberry is different from a shower faucet in myriad ways. The living, conscious senses are not the “sensors” of a non-living machine.

 

Can a computer fly and land an airplane? Yup, they safely do it for millions of people a year. If a computer do that with just "1D data", why can't a human? Serious question. You may say that a human programmed the computer to do it, but that's not the point. Using "1D data", a computer can safely fly and land an airplane. What more evidence do you need that "1D data" can fully represent any geometry we wish? What more evidence do you need that "1D data" is enough to physically traverse space?

It’s not asking questions about the nature of what the information is representing, or questioning the difference between information and its spatial representation. It does not “feel” or “mean.” It is not a living being.

If we don’t know what the dog is, what right do we have to say “we’re only a brain and body?”

Something knows that the image (information is connected to the dog, which means that something in the being has a discerning mechanism that differentiates! "Knows that it knows the difference!" Does that make sense? If it does, then why and how??

 

Needs its own post:

If there are no numbers in a machine/computer, there are no numbers in you, a machine/computer, therefore you should not refer to things coming from your brain as numbers.

yes?