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Merged Artificial Intelligence Research: Supermathematics and Physics

ProgrammingGodJordan

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ProgrammingGodJordan
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Part A - Artificial Intelligence and human-kind, in 2 sentences.

Artificial Intelligence is unavoidably exceeding humans in cognitive tasks, and some projections observe human level brain power in artificial machines/software by at least 2020 (Wikipedia exascale computing source).

Artificial Intelligence is already solving many of human kind's problems.


Part B - Crucial difference between Edward and Tegmark

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

https://futurism.com/human-level-ai-are-probably-a-lot-closer-than-you-think/


Part C - How components approached by Edward's genius applies in AI today

Edward Witten's work concerns some deep stuff on manifolds. (Sample:
https://arxiv.org/abs/hep-th/9411102)

In artificial intelligence, models are observed to be doing some form of manifold representation, especially in the euclidean regime. (And are already demonstrated to be strong candidates for 'disentangling problems' of which many problem spaces occur)

As an unofficial AI researcher myself, I am working on AI, as it relates to super-manifolds.(I recently invented something called 'thought curvature', involving yet another invention of mine called the 'supermanifold hypothesis in deep learning', built atop Yoshua Bengio's manifold work)

So I happen to have a brief, concise description somewhere, where manifolds are shown to non-trivially relate to artificial intelligence (you can see also Deep Learning book by bengio, or Chris Olah's manifold explanation):


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/de-tangling. At zero determinant, unique solutions for scalar multiplications dissolve, when the matrix becomes non-continuous, or non-invertible.

NOTE(i): The state of being "ENTANGLED" is the point before which some de-tangleable classes are de-tangled/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

cfBsLTD.png




Some months ago, I had personally contacted Witten, advising him that his genius could apply in AI. (No response though)
Why does Edward Witten allow his belief (as shown in the video above) to block himself from possibly considerably contributing to artificial intelligence, one of human-kind's most profound tools, even despite contrasting evidence that manifolds apply in machine learning?

///

I have edited this post. The original made excessive use of large fonts and of white space and rose to the level where its formatting was disruptive to the forum. Don't do that. The approach didn't work for Time Cube, and it is not acceptable here.

By the way, the mix of bold, highlight, and red are problematic, too. Let's be more conservative in our typography, please.
Replying to this modbox in thread will be off topic  Posted By: jsfisher
 
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Why the huge fonts, bolding and colours?
 
Typo correction de-tangleable, de-tangled (in Spoiler):

Correction 1: unentangleable
Correction 2: unentangled
 
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[IMGw=900]http://i.imgur.com/cfBsLTD.png[/IMGw]
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.
 
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GlennB said:
Why the huge fonts, bolding and colours?
Click to expand...

For some reason this type of formatting is required of this type of post. I don't know why, but it seems fairly standard for arguments that seek to challenge accepted science with a strange theory proposed by a "under appreciated" genius (often the poster themself, although apparently not in this case).
 
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Giordano said:
For some reason this type of formatting is required of this type of post. I don't know why, but it seems fairly standard for arguments that seek to challenge accepted science with a strange theory proposed by a "under appreciated" genius (often the poster themself, although apparently not in this case).
Click to expand...

(1) The genius I especially underlined in the original post, is Witten.

(2) A degree of math of manifolds, is already apart of machine learning. (So no need for 'challenging accepted science')
 
GlennB said:
That's about coloured text on a coloured background. Here the background is white.
Click to expand...
Or black, if you're using an alternative Tapatalk theme. In general, it is a good principle of web design to let the user control things like text and background color.

This signature is intended to irradiate people.
 
This is a good example of how the exotic colours and fonts detract from the content as that's what we've ended up talking about.

And the margins are busted again.
 
ProgrammingGodJordan said:
However, the spoiler image's style was sufficient.
Click to expand...
Sufficient for what? It's an ugly amateurish mess of an image. I thought Ft1 was FTL so I thought at first it had something to do with faster than light travel. The bit in the middle just looks like some random squiggly lines.

I guarantee that lots of people aren't even going to attempt to make sense of such a mess of a diagram.

Yet you consider it 'sufficient'?

Note that all you've done with your weirdly formatted posts and badly drawn diagrams is help derail the thread into a discussion about how your posts are formatted. That shows you that they are not sufficient, because they're not achieving the goal of communicating to your audience.

Unless, of course, it's your goal to open up a discussion about weirdly formatted internet posts.
 
ProgrammingGodJordan said:
...Some months ago, I had personally contacted Witten, advising him that his genius could apply in AI. (No response though
Click to expand...
Lots of nonsense and then you shoot yourself in the foot :p!
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.
 
ProgrammingGodJordan said:
...manifolds are empirically observed to apply in machine learning:
Click to expand...
There is a manifold hypothesis that has theoretical and experimental support as you cited.
Neural Networks, Manifolds, and Topology
The manifold hypothesis is that natural data forms lower-dimensional manifolds in its embedding space. There are both theoretical3 and experimental4 reasons to believe this to be true. If you believe this, then the task of a classification algorithm is fundamentally to separate a bunch of tangled manifolds.
Click to expand...

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).
 
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.
 
I can psychically sense that this manifold destiny is doomed therefore I don't need to provide evidence for this intuitive conclusion.
 
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