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Merged Artificial Intelligence Research: Supermathematics and Physics

 
fagin said:
Isn't there already a thread on this stuff?
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ProgrammingGodJordan said:
Where else ... entailing Witten and Artificial Intelligence, and belief?
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Thank you. I couldn't be bothered.

Reality Check said:
We covered the ignorant math word salad of "Supermanifold Hypothesis (via Deep Learning)" in another thread.
27 March 2017: A basic point about supermanifolds is they are not actually Euclidean locally.
A more complete explanation of how supermanifolds are not locally Euclidean
24 March 2017 ProgrammingGodJordan: A valid hypothesis is not incoherent math word salad as I pointed out yesterday.
31 March 2017 ProgrammingGodJordan: A web page about a subset of supermanifolds does not state that all supermanifolds are locally Euclidean.
Click to expand...
 
RealityCheck said:
Deep Learning does not mention manifolds in the table of contents you linked to. Manifolds appear at the end of the MACHINE LEARNING BASICS chapter with section 5.11.3 Manifold Learning (page 159).
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PART A


Why bother to comment, given that manifolds are indeed contained in the Deep Learning Book I presented?

Perhaps you had initially commented the highlighted portion, without first reading the book, and because you didn't observe manifolds in the table of contents, you expressed the highlighted portion.

Since manifolds are indeed found in the book, as I had expressed, why bother to express the underlined portion, or better yet, why bother to comment on it at all, (especially when it is clear that I had been valid, in presenting that manifolds..and other related data were in the book)?

Does your capitalizing 'MACHINE LEARNING BASICS' signify something?

Why don't you think a bit longer before posting?



PART B
What has your presentation above to do with the question posed in the original post?
Could you care to attempt to approach the question posed?
 
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RealityCheck said:
You posted some ignorant math word salad on academia.edu. Starts with the title ("Causal Neural Paradox (Thought Curvature): Aptly, the transient, naive hypothesis") and gets worse from there.
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PART A
Look, if you can finally provide scientific evidence as to why the standard math in (thought curvature) is supposedly invalid, do so.

Otherwise what is the point of blathering on absent evidence?

Prediction: RealityCheck shall blather on absent evidence.


PART B
What has your presentation above to do with the question posed in the original post?
Could you care to attempt to approach the question posed?
 
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RealityCheck said:
Lots of nonsense and then you shoot yourself in the foot !
A reason that scientists and mathematicians do not answer every email is that they have filters in place to weed out irrelevant emails, especially from physics and math cranks. Thus your email was probably either irrelevant to Edward Witten or suggested a contact from a physics and math crank. If it was anything like your OP the latter is probable.
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PART A

Here are the contents of my email to Witten:
[imgw=900]http://i.imgur.com/Eo6h2mo.png[/imgw]

Very simple, perhaps too simple?

Edit: Looking back now, perhaps my profile gmail picture was non-desirable.



PART B

Anyway, it is not merely that Edward Witten fails to do what I suggest, but instead, that manifolds are empirically observed to apply in machine learning, and he doesn't select to approach that field, even despite the contrasting manifold AI based evidence.

Physicists aim to unravel the cosmos' mysteries, and so it is a mystery as to why Witten would select not to partake amidst the active machine learning field, especially given that:

(1) AI is one of mankind's most profound tools.

(2) AI is already performing nobel prize level tasks, very very efficiently.

(3) AI may need only be mankind's last invention.
 
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RealityCheck said:
We covered the ignorant math word salad of "Supermanifold Hypothesis (via Deep Learning)" in another thread.
27 March 2017: A basic point about supermanifolds is they are not actually Euclidean locally.


A more complete explanation of how supermanifolds are not locally Euclidean

31 March 2017 ProgrammingGodJordan: A web page about a subset of supermanifolds does not state that all supermanifolds are locally Euclidean.
Click to expand...

Why bother to ignore evidence?

(1)
No where had I supposedly stated that "all supermanifolds are locally Euclidean".

In fact, my earlier post (which preceded your accusation above) clearly expressed that "Supermanifold may encode as 'essentially flat euclidean super space' fabric".

No where above expresses that all supermanifolds were locally euclidean. Why bother to lie?


(2)
Anyway, as I had expressed then, they can be observed to possess some flat Riemannian metric, which entail locally euclidean description.

At any cost, the evidence above already showed your comments to be false.

RealityCheck said:
24 March 2017 ProgrammingGodJordan: A valid hypothesis is not incoherent math word salad as I pointed out yesterday.
Click to expand...

Look, instead of your lies (as demonstrated above), and invalid references (that are built atop the lies), you could just simply demonstrate which part of the math is invalid.

Do that or blather on absent evidence.



FOOTNOTE
What has your presentation above to do with the question posed in the original post?
Could you care to attempt to approach the question posed?
 
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faqin said:
faqin said:
Isn't there already a thread on this stuff?
Click to expand...
ProgrammingGodJordan said:
Where else ... entailing Witten and Artificial Intelligence, and belief?
Click to expand...

Thank you. I couldn't be bothered.
Click to expand...

PART A
And still yet, there is no other thread here, regarding Edward Witten, entailing Manifolds and Machine Learning.

The unavoidable point is that, there is empirical evidence in machine learning, that manifolds apply. (as evidenced in the original post).

RealityCheck's posts (invalid albeit) about my personal work on manifolds/AI don't change the above fact.


PART B
Did you notice that RealityCheck avoided the query in the original post, merely executing cross post information? (where he had long been shown to be invalid, based on publicly available data)
 
JesseCuster said:
[qimg]http://i.imgur.com/cfBsLTD.png[/qimg]
I find it hard to take anything you write seriously when this is the kind of thing you use to illustrate your arguments. It looks like it was scribbled by a 3 year old.

It behooves you to illustrate your work with proper diagrams if you want your readers to engage with you. Putting a diagram like *that* makes it look like you're just not trying and don't care to communicate effectively with your readers.

Inkscape (https://inkscape.org/en/) is free and will allow you to draw proper diagrams. Maybe try learning it and using it.
Click to expand...

Consider the contents of the spoiler presented in the original post:


Points maintain homeomorphisms, such that for any point p under a transition T on some transformation/translation (pertinently continuous, inverse function) t, p0 (p before T) is a bijective inverse for p1 (p after T); on t.

Following the above, topologies maintain homeomorphisms, for any collection of points W (eg a matrix of weights), under some transition T on some transformation/translation sequence (pertinently continuous, inverse functions) s, W0(W before T) is a bijective inverse for W1(W after T); on s, where for any representation of W, determinants are non-zero.

Now, topological homeomorphisms maintain, until linear separation/de-tangling, if and only if neural network dimension is sufficient (3 hidden units at minimum, for 2 dimensional W)

Otherwise, after maintaining homeomorphism at some point, while having insufficient dimension, or insufficient neuron firing per data unit, in non-ambient isotopic topologies that satisfy NOTE(ii) W shall eventually yield zero determinant, thus avoiding linear separation/unentangling. At zero determinant, unique solutions for scalar multiplications dissolve, when the matrix becomes non-continuous, or non-invertible.

NOTE(i): Entangled is the point before which some unentangleable classes are unentangled/made linearly separable.

NOTE(ii): Unique solutions in matrices are outcomes that resemble data sets; for homeomorphisms (topologies: where zero-determinant continuous invertible transformations/translations engender OR ambient isotopies: where positive/nonsingular determinants, nueron permutations, and 1 hidden unit minimum occurs, i.e for 1-dimensional manifold, 4 dimensions are required)

https://www.quora.com/What-is-the-Manifold-Hypothesis-in-Deep-Learning/answer/Jordan-Bennett-9
 
ProgrammingGodJordan: The OP has an idiotic, strawman question

ProgrammingGodJordan said:
...
Click to expand...
Inanely formatted, insulting post not worthy of quoting. Without your irrelevant highlighting of my post:
Reality Check said:
Deep Learning does not mention manifolds in the table of contents you linked to. Manifolds appear at the end of the MACHINE LEARNING BASICS chapter with section 5.11.3 Manifold Learning (page 159).
Click to expand...
I pointed out that your link was ignorant about the book you cited and stopped people wasting their time searching the book for the appropriate page.

Since you want it:
14 August 2017 ProgrammingGodJordan: The OP has an idiotic, strawman question because it is ignorant about Edward Witten.
Edward Witten is not an AI researcher :eye-poppi. The manifolds he studies are those of mathematical physics, e.g. as used in General Relativity.
Edward Witten is probably ignoring your email as one from the many Internet cranks that he receives.
An error about what Edward Witten's opinion. What you quote is the title of Reaching Singularity: Physicist Asserts We Will Never Truly Understand Consciousness written by an editor or reporter.
In an interview with journalist Wim Kayzer, Witten had this to say about our understanding of consciousness:
“Biologists and perhaps physicists will understand much better how the brain works. But why something that we call consciousness goes with those workings, I think that will remain mysterious. I have a much easier time imagining how we understand the Big Bang than I have imagining how we can understand consciousness…

Understanding the function of the brain is a very exciting problem in which probably there will be a lot of progress during the next few decades. That’s not out of reach. But I think there probably will remain a level of mystery regarding why the brain is functioning in the ways that we can see it, why it creates consciousness or whatever you want to call it. How it functions in the way a conscious human being functions will become clear. But what it is we are experiencing when we are experiencing consciousness, I see as remaining a mystery…

Perhaps it won’t remain a mystery if there is a modification in the laws of physics as they apply to the brain. I think that’s very unlikely. I am skeptical that it’s going to be a part of physics.”​
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His opinion that it is a waste of time in physics to study consciousness is a probable reason why he does not study consciousness :jaw-dropp!
 
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ProgrammingGodJordan: Ignorant math word salad on academia.edu (gibberish title, etc)

ProgrammingGodJordan said:
Look, if you can finally provide scientific evidence as to why the standard math ...
Click to expand...
Look at the ignorance of thinking that math is based on "scientific evidence"! What you have is ignorance of mathematics and math gibberish as in a couple of threads.
27 March 2017: A basic point about supermanifolds is they are not actually Euclidean locally.
A more complete explanation of how supermanifolds are not locally Euclidean
24 March 2017 ProgrammingGodJordan: A valid hypothesis is not incoherent math word salad as I pointed out yesterday.
31 March 2017 ProgrammingGodJordan: A web page about a subset of supermanifolds does not state that all supermanifolds are locally Euclidean.

8 August 2017 ProgrammingGodJordan: Ignorant math word salad on academia.edu (gibberish title and worse contents).
 
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ProgrammingGodJordan]: Still does not understand what makes his math gibberish

ProgrammingGodJordan said:
No where had I supposedly stated that "all supermanifolds are locally Euclidean".
Click to expand...
14 August 2017 ProgrammingGodJordan: Still does not understand what makes his math gibberish!
The definition of a supermanifold means that no supermanifold can be locally Euclidean.
There is a subset of supermanifolds that are locally super Euclidean. That means that they have a symmetry group that has operation analogous to the symmetry of Euclidean space. This subset is labeled Euclidean supermanifolds.

Your notation makes your makes gibberish.
14 August 2017 ProgrammingGodJordan: " C∞(Rn)" is not the mathematical notation for any manifold which is M.
For example (what you have read and cited before!): A supermanifold M of dimension (p,q) ...
W.D.Clinger said:
I'd have written "problems", plural, but I'll respond with just one because you wrote the singular.

In your image, you wrote:

C∞ is the set of infinitely differentiable functions, which is not usually regarded as a Euclidean space.

Perhaps you meant the topological space obtained by taking an infinite product of the complex numbers with the standard product topology, but that is not usually regarded as a Euclidean space either.

Then there's the question of what you might have meant by writing C∞(Rn), but (depending on what you meant by C∞) that might well be regarded as a second problem, so I won't bother to mention it or any other problems I may have detected.
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I think that the ISF should create another forum award, named in honor of the op:

The PGJ Gobbledygook Medal.

I have yet to encounter this level of impenetrable technobabble in any other venue.

There's a very good reason why Witten did not respond to PGJ's email.
 
BStrong said:
I think that the ISF should create another forum award, named in honor of the op:

The PGJ Gobbledygook Medal.

I have yet to encounter this level of impenetrable technobabble in any other venue.

There's a very good reason why Witten did not respond to PGJ's email.
Click to expand...

You may recognize science as 'gobbledegook', but science is not gobbledygook.

ProgrammingGodJordan said:
[imgw=800]http://i.imgur.com/Eo6h2mo.png[/imgw]
Click to expand...

It is unavoidable that manifolds are applicable in machine learning, and such is science.
 
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Reality Check said:
Inanely formatted, insulting post not worthy of quoting. Without your irrelevant highlighting of my post:

I pointed out that your link was ignorant about the book you cited and stopped people wasting their time searching the book for the appropriate page.
Click to expand...

Your response above is demonstrably false; that manifolds are indeed contained in the Deep Learning Book I presented, is unavoidable.


Reality Check said:
Since you want it:
14 August 2017 ProgrammingGodJordan: The OP has an idiotic, strawman question because it is ignorant about Edward Witten.
Edward Witten is not an AI researcher :eye-poppi. The manifolds he studies are those of mathematical physics, e.g. as used in General Relativity.
Edward Witten is probably ignoring your email as one from the many Internet cranks that he receives.
An error about what Edward Witten's opinion. What you quote is the title of Reaching Singularity: Physicist Asserts We Will Never Truly Understand Consciousness written by an editor or reporter.

His opinion that it is a waste of time in physics to study consciousness is a probable reason why he does not study consciousness :jaw-dropp!
Click to expand...

No where had I mentioned that Edward Witten was an officially trained artificial intelligence researcher.

...but neither is Max Tegmark, another physicist.

In fact, I underlined that Tegmark was not officially trained AI researcher, but Tegmark presents consciousness as a mathematical problem, and has already contributed important work in machine learning, while Witten unavoidably presented his belief regarding consciousness as a likely never solvable phenomenon:

OriginalPost said:
Edward Witten is quite the human being/physicist.

Max Tegmark is also, quite the human/cosmologist.

Both have phd physics degrees.

The urgent difference?

(1) Max presents consciousness as a mathematical problem... Although Max Tegmark is not an artificial intelligence pioneer nor is officially trained as an artificial intelligence researcher, Max is already contributing important work, helping to organize the theory of deep learning (A hot paradigm in Artificial Intelligence now).

A sample of Max's AI work:https://arxiv.org/abs/1608.08225

Max describing consciousness as a mathematical problem: https://www.youtube.com/watch?v=GzCvlFRISIM


(2) Edward Witten believes we will never truly understand consciousness...

https://www.youtube.com/watch?v=hUW7n_h7MvQ
Click to expand...


It is noteworthy that physicists aim to unravel the cosmos' mysteries, and so it is a mystery as to why Witten would select not to partake amidst the active machine learning field, especially given that:

(1) Manifolds apply non-trivially in machine learning.

(2) AI is one of mankind's most profound tools.

(3) AI is already performing nobel prize level tasks, very very efficiently.

(4) AI may need only be mankind's last invention.
 
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