Beyond AI Today:

imported_IIB

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Feb 20, 2006
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FIRST: Is it possible to post images here?



My theory is that we are already beyond "AI", or we will be very soon.

I'm sure that the "brain in a dish" is old news to most of you, but did any of you stop and think about what if they grew them in enourmous sizes with massive sized arrays of electrodes and in massive arrays in grid topologies with other sophisticated components?

The facts are that they made: 1. Actual chips with live neurons in them, 2. an autonomous robot with rat neuron processor, 3. a art creating "computer", with rat neuron processor, 4. a brain in a dish that LEARNED how to fly an F22 flight simulator (in hurricane force winds), with rat neuron "processors". The latter they did over a year ago, and I cant find any news about what has come after that. While you may not see the significance as the results wernt that aastronomical by some standards, it's important to note that the "brains" learn, and we're getting good at manipulating them.

It's mostly a matter of perfecting the chemistry for optimal processing and lifespan, and perfecting communicating to better interface and teach the 'brains'.

Considering the countless programs by the NSF, DARPA, the entire national university and labratory system, and all of the other federal departments listed in "Converging Technologies for Improving Human Performance" - alone; it's more than safe to say that the government has every intention to do this. If you know your stuff then you'll also know about the fact that the government is converging on all levels(departments, agencies, labratories, universities) to converge for convergenece. Every NIBC related discovery made at the countless labs and such nationwide get fed into the TeraGrid science database, which is right at DARPA's fingertips.
http://www.wtec.org/ConvergingTechnologies/

Who could argue that building these in greater sizes, with sophisticated arrays of them hooked to quantum processors or other more advanced "conventional" processing technologies, wouldnt equate to potential intelligence beyond imagination?

If properly done, this would bypass decades of hardware, and more importanly software development. Many experts say that for every hour of conventional hardware devolopment, it creates 24 hours of software development. Wouldnt Occams Razor here be to go this route? Not that theyd actually stop development on all of the conventional AI technologies, after all its all about knowing 'everything' and converging 'everything' correct?

I figure all they need to do is grow them in larger sizes with electrode arrays covering its entire surfaces using 3D MEA technology.

I think that they would actually do arrays of moderate sized brains, each specially trained for specific tasks all hooked into sophisticated 'conventional' processing equipment, ultimately to have them function as one. Use the true processing equipment(that binds them) to designate each, and adding new levels of processing intelligence that has its own advanced memory features.

Since UofM has sucessfully made quantum processors, and better ones will come, we'll just assume that quantum cpu's would be the heart and "soul" of each "computer".
 

Bobthelost

Diamond Member
Dec 1, 2005
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Originally posted by: IIB
Explain, or can you? If you cant then you're in no position to dismiss it.

You don't know enough about the subject to understand the explanation. :p

I also lack the patience to explain all the details/reasons to you, but watch

I DISMISS IT
 

Bobthelost

Diamond Member
Dec 1, 2005
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Originally posted by: IIB
You assume that I dont know enough. What does assuming mean?


No i stated it as a fact. If you did know enough about it then you wouldn't have put the thread up in the first place.

Or you'd have been smart enough to put it in "highly tecnical" unless you really do want to know which PSU you'll need for these brains in petri dishes?
 

JEDIYoda

Lifer
Jul 13, 2005
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Originally posted by: IIB
You assume that I dont know enough. What does assuming mean?

Actually to be truthful you really don`t know enough about thisa to make a educated comment or opinion.

You posted nothing backing up your claim as to the valadity of your statements....
 

Bootstrap

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Feb 10, 2006
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Everything that you've described in your original post has been done by conventional computers -- reinforcement learning has been used to fly real helicopters upside down (something humans can't do), drive cars, etc. There are also dozens of conferences dedicated to using computers to "create art" (which is an entirely subjective field to begin with). You're assuming that sticking neurons in a box suddenly makes something intelligent, while the truth is that there's still a great deal about the brain and learning that isn't understood. The same thing happened when neural networks were first proposed -- researchers thought, "wow, this sort of looks like a real brain, just think of what we can do!" Then, once they actually studied them and actually understood the mathematics behind how they worked, they realized that they weren't the be all end all of AI. The same thing is happening here.

The technology is certainly interesting, but (a) it's still a long way off, and (b) having a new type of hardware doesn't change the fact that the way we make machines learn still doesn't come close to the ability of humans or animals. So no, I don't think that all they have to do is "grow them in larger sizes with electrode arrays covering its entire surfaces".
 

imported_IIB

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Feb 20, 2006
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Originally posted by: Bootstrap
Everything that you've described in your original post has been done by conventional computers -- reinforcement learning has been used to fly real helicopters upside down (something humans can't do), drive cars, etc. There are also dozens of conferences dedicated to using computers to "create art" (which is an entirely subjective field to begin with). You're assuming that sticking neurons in a box suddenly makes something intelligent, while the truth is that there's still a great deal about the brain and learning that isn't understood. The same thing happened when neural networks were first proposed -- researchers thought, "wow, this sort of looks like a real brain, just think of what we can do!" Then, once they actually studied them and actually understood the mathematics behind how they worked, they realized that they weren't the be all end all of AI. The same thing is happening here.

The technology is certainly interesting, but (a) it's still a long way off, and (b) having a new type of hardware doesn't change the fact that the way we make machines learn still doesn't come close to the ability of humans or animals. So no, I don't think that all they have to do is "grow them in larger sizes with electrode arrays covering its entire surfaces".

Are you talking about neural networks or live neuron networks? There's a huge difference.

a) Don't forget about DARPA, the the TeraGrid science database tha tthey have at heir fingertips.

b) You left out "arrays of", "in grid topologies"

 

Bobthelost

Diamond Member
Dec 1, 2005
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You're postulating evolutionary software development using biological processors rather than silicone based?

Or are you making the deeply stupid assumption that processing power = intelegence.

In short i'm not quite sure what the hell you're trying to discuss at all.
 

imported_IIB

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Feb 20, 2006
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"You're postulating evolutionary software development using biological processors rather than silicone based?"

*No I'm saying they will bypass evolutionary software development by utilizing biological learning components.

"Or are you making the deeply stupid assumption that processing power = intelegence."

In this case it would, neurons and brains learn. 500 quantum or other high end processors wouldn't become intelligent, the internet still isnt even intelligent or self aware. Neurons and brains learn on their own, and it's more than just algorithmic. Conventional processors just crunch number per request.



 

Matthias99

Diamond Member
Oct 7, 2003
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Originally posted by: IIB
"You're postulating evolutionary software development using biological processors rather than silicone based?"

*No I'm saying they will bypass evolutionary software development by utilizing biological learning components.

Um... it's a little more complicated than that.

"Or are you making the deeply stupid assumption that processing power = intelegence."

In this case it would, neurons and brains learn. 500 quantum or other high end processors wouldn't become intelligent, the internet still isnt even intelligent or self aware. Neurons and brains learn on their own, and it's more than just algorithmic. Conventional processors just crunch number per request.

'Neurons' are just specialized cells that behave in certain more or less deterministic ways. Saying a neuron 'learns on its own' is kind of like saying that a transistor 'computes stuff'. Individual neurons can be viewed, in some sense, as just 'number-crunching' elements. Computationally, there is little difference from a computer-modelled neuron element and a biological one.

Brains are a highly organized collection of neurons, just like CPUs are a highly organized collection of transistors. The way brains are organized results in them taking input from external sources, combining it with various feedback loops, and using that to modify the system itself -- what you might call 'learning'. However, it's a long way from a 'learning' system to an 'intelligent' system. And we're a LONG way from building any neuron-based systems that are anywhere NEAR the complexity of the human brain. The sorts of systems used in research right now are in the range of dozens of neurons; even a relatively 'simple' mammalian brain has millions.
 

Bootstrap

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Feb 10, 2006
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You missed the whole point of my post. I was talking about artificial neural networks, and the point still stands. You're assuming that putting real neurons in a computer will suddenly make the computer intelligent. It won't. Neurons by themselves are only capable of representing rather simple mathematical functions. You're just replacing electrical hardware with biological hardware. Humans and animals use complicated networks of real neurons for learning and memory, but we still really don't understand how this works. If we did, we could just as well simulate learning in electrical hardware.

You're treating these groups of real neurons as a "magic" black box, the same way artificial neural networks were originally treated. While interesting, it's not going to be really beneficial until we actually understand what's going on on the inside, and can characterize what the limitations of these networks are. Scientists orignally thought artificial neural networks would be the solution to all learning problems, until they realized that they're just a special type of representation for a nonlinear function.

You said, "You left out "arrays of", "in grid topologies" ". I have no idea what this statement is trying to say. All neural networks, artificial and real, have a network topology, if you want to call it that. The overall layout of the network doesn't change the expressive power of a neural nets in general.
 

Bootstrap

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Feb 10, 2006
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Originally posted by: Matthias99

'Neurons' are just specialized cells that behave in certain more or less deterministic ways. Saying a neuron 'learns on its own' is kind of like saying that a transistor 'computes stuff'. Individual neurons can be viewed, in some sense, as just 'number-crunching' elements. Computationally, there is little difference from a computer-modelled neuron element and a biological one.

Brains are a highly organized collection of neurons, just like CPUs are a highly organized collection of transistors. The way brains are organized results in them taking input from external sources, combining it with various feedback loops, and using that to modify the system itself -- what you might call 'learning'. However, it's a long way from a 'learning' system to an 'intelligent' system. And we're a LONG way from building any neuron-based systems that are anywhere NEAR the complexity of the human brain. The sorts of systems used in research right now are in the range of dozens of neurons; even a relatively 'simple' mammalian brain has millions.

Best explanation in this thread so far.
 
S

SlitheryDee

Crazyness. We're nowhere near that kind of technology. We know few things about neural networks, but saying we're nearly ready to grow gigantic brain-networks and hook them up to quantum computers in order to create some sort of super-intelligent entity(s) is...well it's out there.

That's like thinking you can build a car just because you figured out how to pop the hood :confused:

Edit: I'm no expert in any of the related fields so I could be wrong...
 

Maximilian

Lifer
Feb 8, 2004
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General handware huh? Should be in Highly Technical. Last time i checked the population of anandtech wasent having problems sorting out their rat brain cpu's :p
 

ed21x

Diamond Member
Oct 12, 2001
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we honestly don't know how memory works so far. Right now, we believe that protein based receptors are strengthened through conditioning, and various parts of the brain (eg amygdala, Basal Ganglia) are responsible for different aspects of human emotion. Little by little, we're learning the mechanics of how neurons work, but are still nowhere close to figuring out how people think, feel, and remember. I appreciate you linking to a bunch of scientific articles but they really don't have any direct application to the implications that you are making in your original post. Heck, most of quantum physics is still theoretical, and nobody really believes in string theory.
 

ed21x

Diamond Member
Oct 12, 2001
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Alright, I actually went through that OP article (vaguely skimmed it). Since I'm working here at the VLSB Labs here in the Berkeley BioMedical Engineering department, I honestly know everything that is written in it (it is not a very specific specific article, more like a general Master's thesis).

For those who are too lazy to read it:
All this writeup is, is a collection of articles summarizing the applications of biotechnology in the field of biomimetics, nanotechnolgy, artificial intelligence, Genetics, drug delivery systems, microvalves/pumps and prosthetics.

Nothing pointing to the doomsday prophesy of the original poster. The whole concept of convergence simply states that applications in one field can be applied to another, and thus help to advance biotechnology as a whole.
 

Markbnj

Elite Member <br>Moderator Emeritus
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Sep 16, 2005
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I don't think that the basic premise is outlandish. It's just still in the realm of the highly theoretical. I have no doubt it will happen one day, assuming we get that far. There are a host of problems that aren't addressed by the _extremely_ limited experiments performed so far.

On the other hand, if you want people to take a post like this seriously, avoid sentences like this one:

If you know your stuff then you'll also know about the fact that the government is converging on all levels(departments, agencies, labratories, universities) to converge for convergenece.