Please spare us from truth-seeking and leave that to the philosophers.
In science/engineering we care about instrumentalism, not truth.
All models are wrong. Some are useful.
In science/engineering we care about instrumentalism, not truth.
All models are wrong. Some are useful.
What? Parent is litteraly saying don't trust a model that has no predictive power.
You're saying leave model evaluation to philosophers. Last time we did that we did that we had theory of four elements and phlogiston.
Every model has predictive power. Even the God model.
It predicts something existing; rather than nothing. Of course, it is a worthless prediction but it is a prediction.
I think you mean scientists. I.e., construct an experiment validate, etc.
God model the least possible predictive power imaginable.
Also, according to philosophers, God must exist because it's a perfect being. And a perfect being must exist because it is perfect. They are like people left in a sensory deprivation tank hallucinating random patterns into a sensible picture.
Science does not pursue truth. Philosophy does.
It is still navel gazing batshit insanity, but if it works well enough nobody questions why it doesn’t work better.
Is this a mischaracterization of a subset of your claim: "Scientists do not care if their models are truthful, but they do care that their models are useful."?
The Ptolemaic/geocentric models still work, even if the mathematics are a bit unwieldy.
Truth is a philosophical notion. It is not the concern of science.
I am aligned with model-dependent realism; or epistemic constructivism or thereabouts.
https://en.wikipedia.org/wiki/Model-dependent_realism
https://en.wikipedia.org/wiki/Constructivism_(philosophy_of_...
I don’t have confidence IN my beliefs. I have confidence in the usefulness of my mental toolbox.
On a scale of 0 to 100 how confident are you in your belief of this science?
While this may hold true in almost every case. Just as truth is not absolute, neither is "wrongness".
Furthermore, there exists some model which is neither right nor wrong[1]
[1] https://publications.recursion.is "When all contradictions are resolved what will be left is - an unprovable truth"
Why didn’t you choose dialetheism?
Seems like an arbitrary choice… Could it be that you are culturally biased in the orthodoxy of Western philosophy dating all the way back to Aristotle?
There are systems of reasoning which don’t only concern themselves with Booleans (true and false). There are infinitely many non-Boolean types possible in type theory.
Human constructions/models have many other interesting and desirable qualities/properties beyond “truth” and “falsity”. Mathematicians/Logicians/Computer scientists are deeply interested in understanding those semantic properties.
Recursion is one of those properties studied. It is a foundational concept, not the be all - end all.
Convergence and divergence are another example of interesting semantic properties. They are studied in bifurcation theory.
https://en.wikipedia.org/wiki/Bifurcation_diagram
Whatever your conjecture you are only constructing a lens through which you are interpreting the world.
Why do you point these specific ideas out? I do not, yet, understand the purpose behind your words
From the yardstick of “specificity” my critique of your conjecture is precisely on the grounds that it is too specific; or not general enough.
In particular - the purpose behind my words is to understand why you are constraining thought/expression to merely recursive convergence and to the detriment of recursive divergence.
Why the arbitrary specificity?
In general - I don’t understand the purpose of your conjecture either.
My original paper was not titled Recursion "Convergence" Conjecture, it was titled "Quantum Recursion Postulate". I later realized I was incorrectly conflating popular use of the word "quantum" with "superposition". So, I re-titled my paper.
This felt like a good decision. Convergence is one of the central ideas to the paper-I want others to disprove the paper to converge on a solution. The focus of my paper was not quantum mechanics, nor was the paper describing only a small system. A understandable mistake for someone who has no formal physics background, and has only conversed with those who do.
Of course, this re-titling had the now obvious effect that I lost the diverging aspect of the paper. To further illustrate how I managed to damage the original meaning behind the paper, I will show you perhaps the only proof I have that my conjecture also includes divergence: "The more information considered, the more likely the solution"[1] "Once all is explained, there will always be more perspectives you can attempt to explain that which is already explained from. There will always be new layers to explain previous layers with. Seeking these new layers is what is important, as you can use them to help others understand what you already do. These others, which may want explanations, will stem from these new layers and only understand these new layers."[2]
Looks like I need to change one of my scripts (which I already recorded the audio for >.>) and re-title my paper to the "Recursion Conjecture". Thank you!
Why is it a “recursion conjecture”?
Why isn’t it a “Corecursion conjecture”?
Additionally, I admit that I was not aware of corecursion prior to this conversation. I have been referring to the two as the same concept this entire time. I do not have access to all that is knowable. I did not go to the same universities/* you did that taught this concept. To further illustrate this, "corecursion" has About 18,100 results on Google. "Recursion" has About 20,900,000 results. All YouTube videos on the subject have sub-1k views; since your comment, I have watched many of these videos.
I am prepared to say that corecursion is an integral part to the conjecture; just as important as recursion.
Lastly, it is my understanding that they are, in a way, each other. Ask yourself how you define both and then ask yourself what is the major difference between the two. Are you certain that your definition of both is absolute? Could it be that one could stem from the other in some case? I'll give you a hint, I am being entirely rhetorical. They do stem from one another. Where this stemming-process has *no origin*[3] in an *infinite* system - neither idea can be seen as the "top-level" idea. They are both crucial.
This conclusion may bother you, and I will release a more rigorous argument soon. Corecursion will be a/the topic of one/all of my future videos.
PS: This conversation allowed me to think I understand how type theory integrates with mathematics, to my own personal plague of not internally using concepts I don't think I fully understand
The true nature of reality might be unknowable, but science is a means to move towards it.
Of course scientists care about their models being close to/matching reality. Have you ever spent any amount of time in an university's lab?
Approximately everyone I've met in my alma mater cared about their models being close to reality (or as truthy as they can be).
What scientific procedure would you use to establish whether one working scientific model “matches” reality; while another working model doesn’t? Nobody has direct access to reality outside of their own theoretical paradigm of understanding.
It isn’t just me saying such “crazy” things…
See what model1 gives as a prediction for input X. See what model2 gives as a prediction for input X.
Input X in the world and compare what actually happened.
The models that more closely predict the observations are more likely to reflect reality (aka being closer to the truth).
You don't have direct access to reality. And yet if someone thinks F = ma isn't closer to the truth than F = ma^4 (for the usual symbols and approximations and blah blah, assume I'm aware Einstein existed) then they got way too drunk on other people's philosophies.
Most scientists I met and worked with care if their models are close to reality/truth. Epistemological uncertainty does not mean every model is equally untruthful.
If two different models/theories are observationally equivalent; if two (or more) different curves can be fitted to the same dataset which model is “more true”?
https://en.wikipedia.org/wiki/Observational_equivalence
https://plato.stanford.edu/entries/scientific-underdetermina...
And how do you go from “F=ma for the usual symbols…” to solving the symbol-grounding problem? Symbols are epistemic entities, not ontological entities.
https://en.wikipedia.org/wiki/Symbol_grounding_problem
The model works. That is all there is to be said about it.
If you begin asking questions such as “is the model true or not? Do the terms in the equation correspond to real world entities?” you are no longer doing science, you are doing philosophy.
You don't know which one is more likely to be true (all other things being equal). However, if all else isn't equal and you are well acquainted with a Mr Bayes you can probably do all sorts of fancy Mathematics to estimate which model is more likely to be true. Or just go with your hunch. Or find yourself a dataset that will invalidate one or both of your models.
Mind you, I don't think this is an issue for most subjects. How often do you get different functions that spew the same output in the all observable and theoretical instances?
>If you begin asking questions such as “is the model true or not? Do the terms in the equation correspond to real world entities?” you are no longer doing science, you are doing philosophy
Yes, people often do that when they are engrossed in a subject. Most scientists I met care about the subject they are working on and philosophise a lot about it. Some don't anymore, possibly because working in the academy should be considered a carcinogenic hazard by the World Health Organization.
When talking about scientists people sometimes forget that they are human, often driven towards the career by just wanting to know. They care if their models match / are close to reality to the best of their knowledge.
Do remember that we are talking about scientists, not science. Almost everyone I met in my short time in the academy fundamentally cared if their models closely matched reality. Most of them didn't get where they ended up at for utilitarian reasons, and lots of them are on a permanent state of annoyance at not being able to fill some forms with "I'm just curious" to get funds.
But you still need to tell Mr Bayes what your criteria are for model-selection.
So the output of your calculations is some scalar "truth-value" (higher is better) - what's your input?
In simpler terms: the truthfulness of your model is a function of... what ?
>Mind you, I don't think this is an issue for most subjects. How often do you get different functions that spew the same output in the all observable and theoretical instances?
In curve fitting? Practically all the time! It is a mathematical fact that infinitely many curves fit a finite dataset. So we pick curves that fit approximately, not exactly with the obvious underfitting/overfitting optimisation problem that needs solving in conjunction.