The Ultra Intelligent Machine

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Post by Skyweir »

Not sure how helpful this is but I read an article on machine learning and AI and the differences between the two ..

https://www.forbes.com/sites/bernardmar ... d32b1e2742

Teaching AIs to learn for themselves seems an unreal function given what we have been discussing .. and yet it seems to be the way this tech is progressing.

So you have concepts like teaching AIs or computers to think like humans .. again wow .. do we understand more than we here understand about the way humans think? Process data .. then plugging them into the internet where they can process all the data available .

To my mind there are some great chunks of data available through this medium but there are also a hellova lot of questionable chunks of data on this medium .. so what would a learning, thinking AI make of all that .. and the conflict in "truths" ..

The Neural Networks development is really kinda interesting too.

And then he goes on to his next article Deep Learning and compares this with machine learning.

https://www.forbes.com/sites/bernardmar ... 5c11d726cf

So Deep Learning is about the development of autonomous self teaching systems in AI. Its currently used by google in its voice and image recognition algorithms. As far as predictive learning goes this is another very interesting development .. as a tool for predicting the future. Sounds exciting, then theres this ...

https://www.ibtimes.com/artificial-inte ... er-2452024
Despite the great strides artificial intelligence technology has made in recent years, machines are still woefully below the standard of general intelligence humans function at. One such area is prediction of future actions and events.

Imagine a man running on a racetrack. For humans with their cognitive faculties intact, it is extremely easy to foresee how the next few moments - or even minutes - would play out. For a machine, however, performing this action is a massive problem. If computers can be taught to understand how scenes change and objects interact, it would allow them to get a speculative glimpse of the future - something that is second nature for humans.
In turn, it's probably most helpful to think of Deep Learning as the cutting-edge of the cutting-edge. ML takes some of the core ideas of AI and focuses them on solving real-world problems with neural networks designed to mimic our own decision-making. Deep Learning focuses even more narrowly on a subset of ML tools and techniques, and applies them to solving just about any problem which requires "thought" - human or artificial.

Essentially Deep Learning involves feeding a computer system a lot of data, which it can use to make decisions about other data. This data is fed through neural networks, as is the case in machine learning. These networks - logical constructions which ask a series of binary true/false questions, or extract a numerical value, of every bit of data which pass through them, and classify it according to the answers received.

Because Deep Learning work is focused on developing these networks, they become what are known as Deep Neural Networks - logic networks of the complexity needed to deal with classifying datasets as large as, say, Google's image library, or Twitter's firehose of tweets.

With datasets as comprehensive as these, and logical networks sophisticated enough to handle their classification, it becomes trivial for a computer to take an image and state with a high probability of accuracy what it represents to humans.

Pictures present a great example of how this works, because they contain a lot of different elements and it isn't easy for us to grasp how a computer, with its one-track, calculation-focused mind, can learn to interpret them in the same way as us. But Deep Learning can be applied to any form of data - machine signals, audio, video, speech, written words - to produce conclusions that seem as if they have been arrived at by humans - very, very fast ones. Let's look at a practical example.

Take a system designed to automatically record and report how many vehicles of a particular make and model passed along a public road. First, it would be given access to a huge database of car types, including their shape, size and even engine sound. This could be manually compiled or, in more advanced use cases, automatically gathered by the system if it is programmed to search the internet, and ingest the data it finds there.

Next it would take the data that needs to be processed - real-world data which contains the insights, in this case captured by roadside cameras and microphones. By comparing the data from its sensors with the data it has "learned", it can classify, with a certain probability of accuracy, passing vehicles by their make and model.

So far this is all relatively straightforward. Where the "deep" part comes in, is that the system, as time goes on and it gains more experience, can increase its probability of a correct classification, by "training" itself on the new data it receives. In other words it can learn from its mistakes -just like us. For example it may incorrectly decide that a particular vehicle was a certain make and model, based on their similar size and engine noise, overlooking another differentiator which it determined had a low probability of being important to the decision. By learning that this differentiator is, in fact, vital to understanding the difference between two vehicles, it improves the probability of a correct outcome next time.

So what can Deep Learning do?

Probably the best way to finish this article and give some insight into why this is all so ground breaking is to give some more examples of how Deep Learning is being used today. Some impressive applications which are either deployed or being worked on right now include:

Navigation of self-driving cars - Using sensors and onboard analytics, cars are learning to recognize obstacles and react to them appropriately using Deep Learning.

Recoloring black and white images - by teaching computers to recognize objects and learn what they should look like to humans, color can be returned to black and white pictures and video.

Predicting the outcome of legal proceedings - A system developed a team of British and American researchers was recently shown to be able to correctly predict a court's decision, when fed the basic facts of the case.

Precision medicine - Deep Learning techniques are being used to develop medicines genetically tailored to an individual's genome.

Automated analysis and reporting - Systems can analyze data and report insights from it in natural sounding, human language, accompanied with infographics which we can easily digest.

Game playing - Deep Learning systems have been taught to play (and win) games such as the board game Go, and the Atari video game Breakout.

It is somewhat easy to get carried away with the hype and hyperbole which is often used when these cutting edge technologies are discussed (and particularly, sold). But in truth, it's often deserved. It isn't uncommon to hear data scientists say they have tools and technology available to them which they did not expect to see this soon - and much of it is thanks to the advances that Machine Learning and Deep Learning have made possible.
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Post by Fist and Faith »

Zarathustra wrote:We are trying to simulate intelligence. And we're making progress in this regard. But we never tried simulating consciousness, even the most rudimentary consciousness we see (or assume!) in simple organisms. May that's the problem. Not only do we not know what consciousness is in ourselves, we can't say for sure that other organisms even have it. Maybe they just have complex behaviors and instincts. So if we can't say this for sure in living creatures, how could we ever say it for a computer _ much less build it?
IMO, this is the key to it all, and it's very annoying! :lol: We cannot tell where subjective, non-materially reducible activity starts. Does Euglena want, in even the most rudimentary way, to swim toward the light? Or is it entirely driven by the function of the light photosensitive part and the motion part? (I suppose it could be both - wanting to move toward the light; not having any ability to intentionally make it happen; but going because its systems do what they do anyway.) We don't know. If we knew the simplest thing that experiences non-materially reducible activity, we might figure out the minimum requirements of a rudimentary nervous system. And we might be able to apply that to a bit of programming.

But we can't detect such a thing. Not even in ourselves. Anything we can detect with our various scans is in the realm of the materially reducible, so, by definition, not what we're looking for. All we have left is trying to find it with our own minds, using deduction, reason, logic, whatever we can. Of course, using the mind to find the mind might be problematic.
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Post by wayfriend »

Fist and Faith wrote:Of course, using the mind to find the mind might be problematic.
S'what I've been saying. No matter how hard you examine what you see before you, you never see your own eyes.
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Post by Zarathustra »

I see my eyes everyday. They're hazel. Just sayin'. :P

Smartassery aside, I think we can find ways to explore our minds from either end, both subjective and objective. There will always be something paradoxical about this attempt, but we are making progress.
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Post by Esmer »

can AI ever accomplish Helen Keller?

is the goal of AI to mimic life, or surpass it?

or redefine it?

will it reproduce itself in its own image? if not, by what criteria then?

are we looking at a duplicative process, or a variable one?

you are all missing the very thing required for true artificial intelligence, the one and only thing that makes a blank book a best seller and turns a brain into a mind...


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Post by wayfriend »

Assery aside, one can use a tool (mirror) to gaze upon an image which (after empirical testing) is known to be a flawed (reversed; and wrong perspective) but otherwise useful rendition of one's eyes. This is not the same as seeing your eyes.

Which is the distinction which deserves to be made. What useful, albeit flawed, tool have we devised for perceiving how we think?
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Post by Fist and Faith »

And even without that, I have been told, here, that the subjective nature of our minds makes the task of using it to study itself, or other minds, problematic. A subjective thing studying a subjective thing
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Post by Zarathustra »

Esmer wrote:can AI ever accomplish Helen Keller?
That's an interesting way to phrase the question.

Esmer wrote:you are all missing the very thing required for true artificial intelligence, the one and only thing that makes a blank book a best seller and turns a brain into a mind...
A sense of humor?

The blank book makes for a good punchline, and I agree that wit is a form of intelligence, and humor may be nearly impossible to define with an algorithm (look how much trouble Data had), but I do not think it's absolutely necessary for intelligence, much less consciousness. I know people who don't have much of a sense of humor, and they are certainly conscious and intelligent even when not laughing.

Aside from a good punchline, I'm not sure how the blank book is relevant. It certainly misses the point of my novel metaphor, if it is at all related to that.
WF wrote:Assery aside, one can use a tool (mirror) to gaze upon an image which (after empirical testing) is known to be a flawed (reversed; and wrong perspective) but otherwise useful rendition of one's eyes. This is not the same as seeing your eyes.

Which is the distinction which deserves to be made. What useful, albeit flawed, tool have we devised for perceiving how we think?
And to think we were just discussing the relevance of humor to intelligence! Come on, WF, I was being funny. No need to turn "smartassery" into "assery" just because I disagreed with you.

I understand the point you're making, but my point was relevant in that what we often think of as impossible in principle turns out to be not nearly so in practice. Clearly we are aware of our own self-awareness. Clearly we can analyze it. Phenomenology is one such tool. I recommend the writings of Husserl and Heidegger. There are also various forms of meditation. We have direct access to our own consciousness. We experience it. We can make it an object of our contemplation and study its structures and characteristics. While it's true that this creates a tiered system of consciousness-viewing-consciousness, wherein there will always be a part that is (currently) not an object but rather the ever elusive subject, it is nevertheless analogous to holding up a mirror and seeing your own eyes. If it were impossible to study our own consciousness, then we wouldn't know so much about it.

And, like what we've learned from disecting eyeballs, we have also learned quite a lot about consciousness from brain surgeries, brain injuries, split-brain experiments, etc.
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Post by Skyweir »

Arent assery and smart assery rules of interaction here at the Watch? 🤔

;) :wink:
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Post by Fist and Faith »

But wf asked a good question! "What useful, albeit flawed, tool have we devised for perceiving how we think?" Gotta think outside the box, for sure. But what can be done?

I think any study should be both by and of many people. Since we're talking about interpretations of answers/interactions, we need many people to give their interpretations. Otherwise the results are just one person's interpretation, which is fairly useless.
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Post by Skyweir »

wayfriend wrote:
Fist and Faith wrote:Of course, using the mind to find the mind might be problematic.
S'what I've been saying. No matter how hard you examine what you see before you, you never see your own eyes.
And yet despite the flaws and deficits being identified here .. the work on AIs progresses. The understanding of intelligence, the mind etc progresses ..so scientists are eliciting sufficient data to progress an artifice of the original.
Scientists are also exploring whether consciousness is always a computational process. Some scholars have argued that the creative moment is not at the end of a deliberate computation. For instance, dreams or visions are supposed to have inspired Elias Howe's 1845 design of the modern sewing machine, and August Kekule's discovery of the structure of benzene in 1862.

A dramatic piece of evidence in favor of big-C consciousness existing all on its own is the life of self-taught Indian mathematician Srinivasa Ramanujan, who died in 1920 at the age of 32. His notebook, which was lost and forgotten for about 50 years and published only in 1988, contains several thousand formulas, without proof in different areas of mathematics, that were well ahead of their time. Furthermore, the methods by which he found the formulas remain elusive. He himself claimed that they were revealed to him by a goddess while he was asleep.

The concept of big-C consciousness raises the questions of how it is related to matter, and how matter and mind mutually influence each other. Consciousness alone cannot make physical changes to the world, but perhaps it can change the probabilities in the evolution of quantum processes. The act of observation can freeze and even influence atoms' movements, as Cornell physicists proved in 2015. This may very well be an explanation of how matter and mind interact.

Mind and self-organizing systems
It is possible that the phenomenon of consciousness requires a self-organizing system, like the brain's physical structure. If so, then current machines will come up short.

Scholars don't know if adaptive self-organizing machines can be designed to be as sophisticated as the human brain; we lack a mathematical theory of computation for systems like that. Perhaps it's true that only biological machines can be sufficiently creative and flexible. But then that suggests people should - or soon will - start working on engineering new biological structures that are, or could become, conscious.
The things that make us self-conscious aren't as flattering as the delusion of ego or the illusion of self-permanence. Self-consciousness isn't even very useful (which is why research into consciousness rarely goes anywhere-it spends too much time assuming there's a grand purpose and then searching for it).
With the concept of Theory of Mind firmly in our thoughts, and the knowledge that brain modules are both fallible and disconnected, we are primed to understand human consciousness, how it arose, and what it's (not) for.

This may surprise those who are used to hearing that we don't understand human consciousness and have made no progress in that arena. This isn't true at all. What we have made no progress in doing is understanding what human consciousness is for.

Thousands of years of failure in this regard points to the simple truth: Human consciousness is not for anything at all. It serves no purpose. It has no evolutionary benefit. It arises at the union of two modules that are both so supremely useful that we can't survive without either, and so we tolerate the annoying and detrimental consciousness that arises as a result.
And if self consciousness is not an aspect of particular value ..does it even matter if indeed it is limited to carbon based life forms only? Alternatively perhaps it is Vs cyborgs or sci fis Cylons .. which will secure consciousness?
... consciousness may be limited to carbon substrates only. Carbon molecules form stronger, more stable chemical bonds than silicon, which allows carbon to form an extraordinary number of compounds, and unlike silicon, carbon has the capacity to more easily form double bonds. This difference has important implications in the field of astrobiology, because it is for this reason that carbon, and not silicon, is said to be well-suited for the development of life throughout the universe.
But it would seem that not ALL parts of the human brain or mind .. may even be necessary re future technology re machines, AIs .. what have you ____
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Post by Fist and Faith »

Skyweir wrote:
wayfriend wrote:
Fist and Faith wrote:Of course, using the mind to find the mind might be problematic.
S'what I've been saying. No matter how hard you examine what you see before you, you never see your own eyes.
And yet despite the flaws and deficits being identified here .. the work on AIs progresses. The understanding of intelligence, the mind etc progresses ..so scientists are eliciting sufficient data to progress an artifice of the original.
There is not progress on artificial consciousness. There is no suspicion that consciousness has been created, much less self-consciousness. And I strongly disagree that self-consciousness is not very useful.
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Post by Zarathustra »

Fist and Faith wrote:But wf asked a good question! "What useful, albeit flawed, tool have we devised for perceiving how we think?" Gotta think outside the box, for sure..
yes it was a good question. I thought I gave some good answers
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Indeed. I withdraw my statement. But I'm still trying to find objective things. Everything I hear about consciousness is what it isn't.
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Post by wayfriend »

Self-contemplation should be ruled out as any sort of reliable tool for understanding how consciousness functions. It can be neither objective nor independent. It's not without use, but it's not the kind of tool we need.
Skyweir wrote:But it would seem that not ALL parts of the human brain or mind .. may even be necessary re future technology re machines, AIs .. what have you

Undoubtedly. I'm in the camp that believes that our minds have a lot of evolutionary vestiges which may no longer be necessary or are necessary only for odd things not related to thought or consciousness. Not to mention that what is left may work inefficiently or poorly. Any artificial consciousness may be more "pure", in the sense of having only directly essential components which always function perfectly. That's the way that "artificial" beats "natural". But the question is: what's actually inessential? E.g. do we need a sense of shame to be conscious?

This news is relevant: Scientists Find a Strange New Cell in Human Brains: The 'Rosehip Neuron'. To cut to the chase: humans may have a kind of neuron other species don't have. Think about that!
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wayfriend wrote:Any artificial consciousness may be more "pure", in the sense of having only directly essential components which always function perfectly. That's the way that "artificial" beats "natural". But the question is: what's actually inessential? E.g. do we need a sense of shame to be conscious?
Not knowing the answers to so many questions about consciousness makes me sceptical that we'll be able to make one with only directly essential components.

And I've also heard that a lot of programming has non-essential code. Dead code, or junk code? Sometimes notes that the programmer wrote for reference? Sometimes old stuff that isn't needed for the upgrade, but isn't removed?
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Fist and Faith wrote:And I've also heard that a lot of programming has non-essential code. Dead code, or junk code? Sometimes notes that the programmer wrote for reference? Sometimes old stuff that isn't needed for the upgrade, but isn't removed?
That's absolutely true. But only when $$$ demands that the same code be used for a long time, adding more and more function, and when $$$ resists spending the time to clean it up. There's no profit in cleaning up code that already works.

In a way, money adds Darwin to commercial software. Vestiges are not eliminated until they incur a survival penalty.

In a scientific, rather than a commercial, environment, things are more controlled.
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I think it is highly likely possible, and quite close to happening, to create a machine that achieves nearly everything we would call "intelligent" within narrow ranges, and many things we'd call intelligent in broader ranges, without actually being intelligent, let alone conscious, in a global sense.

That's already happened in extremely narrow ranges.

As far as testing a machine for real intelligence...one advantage we have with the machines is we, and "they" have total access to the code. We know what code is, we know how code works, and we can copy and paste it, and experiment on/with it in/with hundreds, thousands, millions of ways without in any way damaging/harming/altering the original...and without the waste/ethical problems involved in making hundreds/thousands/millions of Vat-Vraiths and torturing them with "controlled experiments."
AND, that turns self-contemplation into an amazingly useful tool...at least for the AI, we'll have to get way further down the cyber path for it to work for people...cuz the machine can do it to itself.

Here's what I see as the unaddressed [as far as I know] difficulty.
[[not unrecognized...just no one has come up with a great way to approach it]]:

EVERY ONE of these machines, and all possible ones right now [even the supposed quantum ones] function, at root, on logic-based fundamentals...logical rules.
But living things DON't run on those. Even non-living things don't run on those.
There are no logics/maths without axioms and abstractions...and they require no existence, and admit no forces/materials.
The universe has no axioms, it irreducibly concrete...and exitence/forces are absolute necessities.
The sidelining of those things [[I think because people have tried and found it intractable, so most have given up]] leads to the popular [in many sectors] acceptance of the notion of the "unreasonable effectiveness of mathematics."
I've said before...it isn't unreasonable, and one can only claim "effective" because all the ineffective parts are IGNORED.

The point? This:
Something very like intelligence will probably come from machines...hell, in some ways already has. Consciousness probably won't without a total revolution.
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Post by Fist and Faith »

OK, I want to get back to how to my idea of evolution. I would not imagine a program can replicate itself with absolute precision. Am I wrong about that? Can we make a program that is perfect in this way?

So write a program that replicates itself when the command is given. Then both copies will replicate themselves when the command is given. Then four copies, etc.

Errors will creep in. Some will not have an affect that will be noticed. But, eventually, some will prevent the program from receiving the command, and others will prevent it from replicating itself. Put pressure on the system, and have a second program that eradicates programs that don't replicate after the command has been given.

Of course, we'll need more. What would a "good" mutation mean? In what way could it be good? How could it benefit the program, and give it an advantage over the copies that don't have it?
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Vraith wrote:I think it is highly likely possible, and quite close to happening, to create a machine that achieves nearly everything we would call "intelligent" within narrow ranges, and many things we'd call intelligent in broader ranges, without actually being intelligent, let alone conscious, in a global sense.
Absolutely agree. I like the way you phrased it. A machine which is not actually intelligent, but which produces outcomes as if it were.
Fist and Faith wrote:I would not imagine a program can replicate itself with absolute precision. Am I wrong about that?
Biological beings don't "copy". They "merge" - half of one, half of the other, randomly shuffled. And they don't merge themselves, they merge their "blueprints", from which new beings must grow. Being physical and complex, errors can creep in due to (for example) solar radiation at any stage of this.

A program would replicate itself with perfect precision. That's an artifact of being digital.

But there's actually two parts to this, the program and the data. The program is the instructions, and the data is like the memory and experiences and whatever it learned of it's own accord.

If you copy the program and not the data, then you have another "being" which is exactly as intelligent but which is a different "person", having to learn things all over again, and capable of having a different "personality".

But if you copy the data ... then you have two copies of the same "person", where both believe that they are the original, possibly leading to disastrous consequences.

That being said,

It is possible that biological beings might have been designed so that only one parent is necessary. Just use the DNA from one organism instead of mixing from two. Then proceed in the usual way. However, this didn't happen - whether it be intelligent design or divine intervention or darwinian selection or something else - DNA doesn't work that way. And the beauty is, because the result is not a direct copy, we CAN evolve. (Of course, it also requires a lot of killing off of the non-optimal variations.)

Since its so important, we could figure out a way to do something similar to our intelligent machines. Mix them up. Cull all but the improved. It would be artificial and arbitrary rather than random and uncontrolled. But it would be similar.
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