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Old 15th March 2017, 07:34 AM   #321
ProgrammingGodJordan
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Originally Posted by MikeG View Post
If you think that slurring your interlocutors in this conversation is a good way forward then you will soon fall foul of the rules. We aren't "beings", and I am not slow. It was you who wrote "10^15 is roughly 10^16". We've had long conversations about it.............have you forgotten already?

Show us one instance (if possible) of the thing of which you are accusing me.

I wasn't calling you slow, I expressed that persons' writings tended to contain a lack of understanding, as their writings seem to be slow to contain information as I had posted throughout this thread.

Edit: I shall slumber now. Proceed to attempt to discover evidence as you accuse me.

Last edited by ProgrammingGodJordan; 15th March 2017 at 07:40 AM.
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Old 15th March 2017, 07:39 AM   #322
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Originally Posted by ProgrammingGodJordan View Post
.......
I wasn't calling you slow, I expressed that persons' writings tended to contain a lack of understanding, as their writings seem to be slow to contain information as I had posted throughout this thread.
Yeah yeah. You think we were born yesterday?
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Old 15th March 2017, 07:45 AM   #323
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Originally Posted by ProgrammingGodJordan View Post
Show us one instance (if possible) of the thing of which you are accusing me.......
OK. That was easy:

Originally Posted by ProgrammingGodJordan View Post
10^15 is listed in the source of the original post

Roughly 10^16 was mentioned............
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Old 15th March 2017, 07:49 AM   #324
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Originally Posted by MikeG View Post

Originally Posted by ProgrammingGodJordan
Show us one instance (if possible) of the thing of which you are accusing me.......

OK. That was easy:

Originally Posted by ProgrammingGodJordan
10^15 is listed in the source of the original post
Roughly 10^16 was mentioned............


Yes, the above event was an easily foolish writing of yours. (As predicted)

At value 10^15 synapses (original post Wikipedia source koch value) we have 10 impulses per second, to yield 10^16 synaptic operations per second.

So 10^15 synapses, is roughly 10^16 synaptic ops per second.



PS:
There is a distinction between the units. Recall that 10^16 synaptic ops per sec were mentioned in original post, and 10^15 synapses was also in the source Wikipedia linked on original post.

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Old 15th March 2017, 07:55 AM   #325
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Originally Posted by ProgrammingGodJordan View Post
Yes, that was easily foolish writing of yours.

At value 10^15 synapses (original post Wikipedia soucr koch value) we have 10 impulses per second, to yield 10^16 synaptic operations per second.

So 10^15 synapses, is roughly 10^16 synaptic ops per second.
No PGJ. Go back to the original. You'll find you were pages away from playing that particular gambit at the stage of the above post.

Stop with the sophistry. Do you think we haven't seen sophistry here for ever? You're argument has gone from silly to ludicrous, you can't back up your claims, and you adjust Wiki to try to score internet points in this thread........so what is your response? Sophistry. Wriggle around trying not to get caught slurring us, but all you are doing is highlighting the paucity of content in your OP and follow-up claims. You've got nothing, so you abuse us.
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Old 15th March 2017, 07:55 AM   #326
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Why not look at something more recent and clearer?
http://p9.hostingprod.com/@modha.org...mputing_2.html

This gives 1.05x1012 synapses in 2016. 256 million per chip x 4096 cores
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Old 15th March 2017, 08:04 AM   #327
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Originally Posted by MikeG View Post
No PGJ. Go back to the original. You'll find you were pages away from playing that particular gambit at the stage of the above post.

Stop with the sophistry. Do you think we haven't seen sophistry here for ever? You're argument has gone from silly to ludicrous, you can't back up your claims, and you adjust Wiki to try to score internet points in this thread........so what is your response? Sophistry. Wriggle around trying not to get caught slurring us, but all you are doing is highlighting the paucity of content in your OP and follow-up claims. You've got nothing, so you abuse us.
Your writings grossly miss the point. (As usual)

(1)
If you look at the relevant original post wiki url, 10^15 synapses was a part of the original post wiki link, that referred to koch.

(2)
If you look at the original post text, I mentioned 10^16 synaptic operations per second.


Recall that I have not edited the original post, that contains all the references made above.


See the above however you choose.

Last edited by ProgrammingGodJordan; 15th March 2017 at 08:19 AM.
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Old 15th March 2017, 08:10 AM   #328
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Originally Posted by Wudang View Post
Why not look at something more recent and clearer?
http://p9.hostingprod.com/@modha.org...mputing_2.html

This gives 1.05x1012 synapses in 2016. 256 million per chip x 4096 cores
It is optimal that you researched on IBM's latest efficient chips. This relates with the video I posted 5 pages ago.

Last edited by ProgrammingGodJordan; 15th March 2017 at 08:15 AM.
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Old 15th March 2017, 08:10 AM   #329
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Originally Posted by ProgrammingGodJordan View Post
No.

Read carefully.

I expressed that ibm achieved 10^14, and they did just that.

IBM: "We have simulated an unprecedented 2.084 neurosynaptic cores containing 53 x 1010 neurons, and 1.37 x 1014 synapses."

http://www.modha.org/blog/SC12/RJ105...000=1489540048

Your writings show blindness in more ways that one.
More spam of the same link. Repetition does not create truth.
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Old 15th March 2017, 08:13 AM   #330
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Originally Posted by abaddon View Post
Originally Posted by ProgrammingGodJordan View Post
No.

Read carefully.

I expressed that ibm achieved 10^14, and they did just that.

IBM: "We have simulated an unprecedented 2.084 neurosynaptic cores containing 53 x 1010 neurons, and 1.37 x 1014 synapses."

http://www.modha.org/blog/SC12/RJ105...000=1489540048

Your writings show blindness in more ways that one.

More spam of the same link. Repetition does not create truth.
To clarify, what do you suppose that I distorted in the above sequence you quoted?

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Old 15th March 2017, 08:33 AM   #331
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Originally Posted by ProgrammingGodJordan View Post
To clarify, what do you suppose that I distorted in the above sequence you quoted?
What? I never made any such claim. I simply stated with proof that you are spamming the same link over and over.
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Old 15th March 2017, 09:27 AM   #332
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Originally Posted by ProgrammingGodJordan View Post
It is optimal that you researched on IBM's latest efficient chips. This relates with the video I posted 5 pages ago.
Do you work for IBM, PGJ? Why are you so interested in their stuff, yet, for instance, ignored the stuff about the more advanced Chinese computers a few pages back?
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Old 15th March 2017, 09:29 AM   #333
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Originally Posted by ProgrammingGodJordan View Post
Your writings grossly miss the point. (As usual)........
And you grossly miss the point. We were talking about your use of the word roughly.
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Old 15th March 2017, 09:41 AM   #334
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Originally Posted by ProgrammingGodJordan View Post
I don't ask anyone to do anything.

I still observe my prior reply in post #307.

Its time to focus on the paper in the original post.

If you lack the mental awareness/experience to deal with the paper, move on to another thread, otherwise do criticize the above paper, as technically as possible.
I love how the first sentence of this post is you claiming that you don't ask anybody to ignore the fact that you based your conclusions on evidence gathered from a paper which you admit that you didn't read properly, and the next three sentences are you asking people to ignore the fact that you based your conclusions on evidence gathered from a paper that you didn't read properly.
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Old 15th March 2017, 05:24 PM   #335
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Originally Posted by ProgrammingGodJordan View Post
Criticism is welcome/needed.
(i) Irrelevant opinion.
(ii) Argument by YouTube video is usually invalid
(iii) Brain speed is not "optimization".
(iv) Computer speed is not artificial intelligence.
(v) A badly (madly?) titled PDF on the internet is dubious, especially on a site that you have to register to download the PDF. "Causal Neural Paradox (Thought Curvature): Aptly, the transient, naive hypothesis" is nonsense.

The idea seems to be that increases in computer speed (e.g. quantum computing) will magically lead to something called "super artificial intelligence". Aided by an IBM chip?

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Old 15th March 2017, 05:44 PM   #336
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Originally Posted by ProgrammingGodJordan View Post
Sources will vary human brain speed from roughly 10^16 to 10^18 synaptic operations per second.
It is standard in science and common in real life that a calculation on a range of values does not use the extremes or values outside of that range. The reasonable value to use is a value in the middle of the range. That is usually the average or median value.

You gave no source for "roughly 10^16 to 10^18 synaptic operations per second" so a reasonable value would be 10^17 synaptic operations per second.
10^14 computer operations a second gets to the lower limit of the range that you gave in a little over 8 years (doubling every 2 years), i.e. at least 2025.

Moore's law may be running up against physical and economic constraints - some experts think that the rate of increase is decreasing.

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Old 15th March 2017, 06:04 PM   #337
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Originally Posted by ProgrammingGodJordan View Post
Some items follow:
Those items are irrelevant spamming of the thread with non-science github links !.
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Old 15th March 2017, 06:15 PM   #338
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Originally Posted by ProgrammingGodJordan View Post
At value 10^15 synapses (original post Wikipedia source koch value) we have 10 impulses per second, to yield 10^16 synaptic operations per second.
A small nitpick: That should be 10^16 synaptic impulses per second .
Using the correct units of measurement is important in science, e.g. 10 meters per second * 10^16 seconds has to give meters, not feet.
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Old 15th March 2017, 06:33 PM   #339
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Originally Posted by ProgrammingGodJordan View Post
You slightly mangled and cut out the context of that quote from the PDF.
Quote:
Since the final submission of our work on the Compass scalable simulator for the IBM True North Cognitive Computing architecture [1], we have simulated an unprecedented 2.084 neurosynaptic cores containing 53 x 1010 neurons, and 1.37 x 1014 synapses, running at only 1542x slower than real time.
There is no "We...synapses." sentence.
This is a simulation on an IBM Sequoia (also see IBM Blue Gene/Q) supercomputer, not a chip. It cannot be compared to a chip because it is massively parallel (98,304 compute nodes).

The OP links to a 2014 IBM SyNAPSE chip with "only" 256 million synapses.
More current research from IBM has been cited: Breaking News: Supercomputing 2016 Paper -- TrueNorth Ecosystem for Brain-Inspired Computing
Quote:
Finally NS16e, the scale-up system, has a tightly connected 16-chip TrueNorth array. It can run a neural network using up to 16 million neurons and 4 billion synapses. This system can run image recognition tasks (CIFAR 10, CIFAR 100) with near state-of-the-art accuracy at over 1000 frames per second.

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Old 15th March 2017, 07:57 PM   #340
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Originally Posted by Reality Check View Post
A small nitpick: That should be 10^16 synaptic impulses per second .
Using the correct units of measurement is important in science, e.g. 10 meters per second * 10^16 seconds has to give meters, not feet.
Worthless comment.

"10 impulses per second" is derived from the works of neuroscientists.

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Old 15th March 2017, 07:58 PM   #341
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Originally Posted by Reality Check View Post
Those items are irrelevant spamming of the thread with non-science github links !.
Garbage comment.

You may have misses it, but artificial neural networks is a part of modern science.
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Old 15th March 2017, 08:01 PM   #342
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Originally Posted by Reality Check View Post
(i) Irrelevant opinion.
(ii) Argument by YouTube video is usually invalid
(iii) Brain speed is not "optimization".
(iv) Computer speed is not artificial intelligence.
(v) A badly (madly?) titled PDF on the internet is dubious, especially on a site that you have to register to download the PDF. "Causal Neural Paradox (Thought Curvature): Aptly, the transient, naive hypothesis" is nonsense.

The idea seems to be that increases in computer speed (e.g. quantum computing) will magically lead to something called "super artificial intelligence". Aided by an IBM chip?
The above is heavily garbage bound.


(1)
Thought curvature concerns manifolds.
You may have been unaware, but manifolds are potential solvers of severe discrimination issues in modern machine learning.

Each entity in the problem space is observable as detangleable manifolds.


(2)
I didn't express that computer speed was the only thing.

Instead, I mentioned that computer speed was core to the success of modern machine learning.



(3)
Now, the human brain is efficient per general intelligence. (Compared to other brain like constructs)

This efficiency has something to do with how many cycles per frame exist per material.



(3)
10^14 artificial synaptic operations per second are currently done by machines.

As these machines got more powerful, they did more and more cognitive tasks. (Some exceeding human intelligence)

It doesn't take a genius to see that with some number of advancements per power/structure, overall artificial human level intelligence is inevitable.

Last edited by ProgrammingGodJordan; 15th March 2017 at 08:11 PM.
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Old 15th March 2017, 08:04 PM   #343
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Originally Posted by ProgrammingGodJordan View Post
Worthless comment.
Pointing out basic science is never worthless: Dimensional analysis.
Followed by an actually worthless comment from you . I have read the thread and know where that number comes from.
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Old 15th March 2017, 08:08 PM   #344
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Originally Posted by ProgrammingGodJordan View Post
You may have misses it, but artificial neural networks is a part of modern science.
You have missed the fact that github is not scientific literature ! And that artificial neural networks is not the subject of this thread - it is some undefined ""nave approach ".

Thus: Those items are irrelevant spamming of the thread with non-science github links!

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Old 15th March 2017, 08:11 PM   #345
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Originally Posted by ProgrammingGodJordan View Post
The above is heavily garbage bound.
Calling the real world garbage is not wise. In the real world the OP contains:
Originally Posted by Reality Check View Post
(i) Irrelevant opinion.
(ii) Argument by YouTube video is usually invalid
(iii) Brain speed is not "optimization".
(iv) Computer speed is not artificial intelligence.
(v) A badly (madly?) titled PDF on the internet is dubious, especially on a site that you have to register to download the PDF. "Causal Neural Paradox (Thought Curvature): Aptly, the transient, naive hypothesis" is nonsense.
A point I am trying to make is that you have not yet described your "naive approach" after a couple of days and 345 posts.

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Old 15th March 2017, 08:14 PM   #346
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Originally Posted by Reality Check View Post
You have missed the fact that github is not scientific literature !
And that artificial neural networks is not the subject of this thread - it is some undefined ""nave approach ".

Thus: Those items are irrelevant spamming of the thread with non-science github links!

Deepmind is the planet's prominently powerful artificial Intelligence.

Deepmind atari q, is on github.

From that paradigm, advancements were made.

Gihub or not, neural code is science.
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Old 15th March 2017, 08:16 PM   #347
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Originally Posted by Reality Check View Post
Calling the real world garbage is not wise. In the real world the OP contains:


A point I am trying to make is that you have not yet described your "naive approach" after a couple of days and 345 posts.
This does not perturb the gihub links' contents to suddenly become non science.

The description of the naive approach is contained in the paper/code, from the original post.
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Old 15th March 2017, 08:19 PM   #348
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Originally Posted by ProgrammingGodJordan View Post
You may have been unaware, but manifolds are potential solvers of severe discrimination issues in modern machine learning.
Manifolds are a wonderful mathematic concept I first came across when learning General Relativity and I do know about their use in machine learning.
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Old 15th March 2017, 08:22 PM   #349
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Originally Posted by Reality Check View Post
It is standard in science and common in real life that a calculation on a range of values does not use the extremes or values outside of that range. The reasonable value to use is a value in the middle of the range. That is usually the average or median value.

You gave no source for "roughly 10^16 to 10^18 synaptic operations per second" so a reasonable value would be 10^17 synaptic operations per second.
10^14 computer operations a second gets to the lower limit of the range that you gave in a little over 8 years (doubling every 2 years), i.e. at least 2025.

Moore's law may be running up against physical and economic constraints - some experts think that the rate of increase is decreasing.
(A)
Based on my original post's source, you can find an estimation of 10^15 synapses

At 10^15 synapses, we have 10 impulses per second, which yields 10^16 sops.


(B)
I had long discussed that Moore's law was decreasing.

Moore's law ends soon after 2020. (Hence the 2020 calculation was pertinent)

Regardless, any rate of improvement of machines shall probably yield artificial human level intelligence.
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Old 15th March 2017, 08:22 PM   #350
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Originally Posted by ProgrammingGodJordan View Post
This does not perturb the gihub links' contents to suddenly become non science[
A collection of code is not scientific literature, i.e. non-science.
I am not going to register at a web site to download an incoherently titled PDF.
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Old 15th March 2017, 08:23 PM   #351
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Originally Posted by ProgrammingGodJordan View Post
Deepmind ....
Gituib is still not scientific literature.
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Old 15th March 2017, 08:30 PM   #352
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Originally Posted by ProgrammingGodJordan View Post
(A)...
Read the OP: If mankind isn't erased (via some catastrophe), on the horizon of Moore's Law, mankind will probably create machines, with human-level brain power (and relevantly, human-like efficiency), by at least 2020.

Based on your numbers and Moore's law that claim is invalid. If Moore's law decreases then the claim is even more wrong.
Though you may want to clarify what "on the horizon of Moore's Law" means. It sounds like you expect it the law stop in 2020 and the number of transistors per chip to remains constant forever .

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Old 15th March 2017, 08:30 PM   #353
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Originally Posted by Reality Check View Post
Manifolds are a wonderful mathematic concept I first came across when learning General Relativity and I do know about their use in machine learning.
That's fine.

...but as I mention, it is common enough in machine learning.

At basis, each x ~ P may be observed as some manifold.

The problem then becomes separation of manifolds, such that unique solutions are discoverable for some dataset/input range, where each matrix representation is a bijective inverse for some following representation, on some continuous function sequence.

In other words, we have a detangling problem.

This is at least the sketch at the manifold level.

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Old 15th March 2017, 08:35 PM   #354
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Originally Posted by Reality Check View Post
I did the calculations over some range a * 10^15 synapses, on Moore's law 2 years per minimization cycle.

So, the calculations holds while Moore's law is still alive.

Regardless, super intelligence is probably inevitable, given any rate of improvement over speed and or programming/architecture.
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Old 15th March 2017, 08:36 PM   #355
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Originally Posted by ProgrammingGodJordan View Post
...This is at least the sketch at the manifold level.
A basic sketch stating what is known does not create super artificial intelligence.
ETA: Even a cartoon does not create super artificial intelligence .

Last edited by Reality Check; 15th March 2017 at 08:45 PM.
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Old 15th March 2017, 08:43 PM   #356
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Originally Posted by ProgrammingGodJordan View Post
So, the calculations holds while Moore's law is still alive.
The actual calculation shows that it is impossible to achieve your claim by 2020 of roughly 10^16 to 10^18 synaptic operations per second.
The OP links to a 2014 IBM SyNAPSE chip with "only" 256 million synapses.
A claim of 10^14 computer operations a second gets to the lower limit of the range that you gave in a little over 8 years (doubling every 2 years), i.e. at least 2025. But your source for this is not an currently working chip - it is a simulation on a massively parallel supercomputer.

The rest of the post may need a Duh! because it is just about inevitable that we will have "a brain in a box" sometime - maybe within the next few decades.

Last edited by Reality Check; 15th March 2017 at 08:51 PM.
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Old 15th March 2017, 08:47 PM   #357
ProgrammingGodJordan
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Originally Posted by Reality Check View Post
The actual calculation shows that it is impossible to achieve your claim by 2020 of roughly 10^16 to 10^18 synaptic operations per second.

The rest of the post may need a Duh! because it is just about inevitable that we will have "a brain in a box" sometime - maybe within the next few decades.
I don't see how 10^14 synapses for current machine level, and human 10^15 synapses = 10^16 sops fail to yield 2020 year, applying H = K * 2n.
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Old 15th March 2017, 08:50 PM   #358
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Originally Posted by Reality Check View Post
A basic sketch stating what is known does not create super artificial intelligence.
ETA: Even a cartoon does not create super artificial intelligence .
Here is slightly better description, in loose machine learning terms:
  • 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 in network)



Last edited by ProgrammingGodJordan; 15th March 2017 at 09:00 PM.
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Old 15th March 2017, 09:00 PM   #359
Reality Check
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Originally Posted by ProgrammingGodJordan View Post
I don't see how 10^14 synapses for current machine level, ...
I added some text to the posts you replied to but I will emphasize this:
10^14 synapses for current machine level wrong because no current machine has 10^14 synapses.

Even with this imaginary 10^14 synapse machine, you fail to get to 2020.
10^14 * 10 = 10^15 synaptic operations per second.
Double this to get to 2019: 2 * 10^15 synaptic operations per second.
Double this to get to 2021: 4 * 10^15 synaptic operations per second.
That is less than half of the lower limit of your claim. So the claim is debunked even if we ignore the reasonable interpretation of "roughly" + a range as meaning "somewhere in that range" !

Even worse, the mostly likely value in a range of values in the middle of the range, thus:
It is standard in science and common in real life that a calculation on a range of values does not use the extremes or values outside of that range

Last edited by Reality Check; 15th March 2017 at 09:02 PM.
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Old 15th March 2017, 09:06 PM   #360
Reality Check
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Originally Posted by ProgrammingGodJordan View Post
Here is slightly better description,...:
Random highlighting does not make a better description of anything. What might be a cut and paste from a textbook is a waste of space - link to the source.

ETA: looks more like a cut an paste from here which hints of out of context, mathematic word salad from an amateur.

Last edited by Reality Check; 15th March 2017 at 09:11 PM.
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