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Machines That Emulate The Human Brain
prostoalex writes "Discover magazine provides an interesting insight into the future technologies that will emulate the human brain. While artificial intelligence supporters always considered direct emulation of brain functions too complex and preferred the top-down approach, some people are researching the ways human brain processes data. One of the interesting discoveries, mentioned in the article, is ability of the brain to re-architect the links as new information is added."
if we want to analyse how alcohol impairs our thinking, how do we get these things drunk?
Can a male emulation understand female emulation wishes?
NEOCA - Custom LED Flashlights
What would the machine do if it were intelligent enough? Men/women atleast would do things that make 'em happy. What can a machine be happy about? ,right? ( assuming that a bee's brains are equivalent to a small cluster of human brain ?) . Now would the bees still look for honey more itelligently? or would they find the grand unified theory?
Also if this rewiring theory is true, we could just put in nano-radios into the head of a zillion bees and put in a nice enough routing algorithm then the bee colony would be an intelligent being
.ACMD setaloiv siht gnidaeR
or are the four facial expressions analyzed:
smirk, smirk, smirk, smirk
?
Joe
http://www.joegrossberg.com
Maybe I'm getting old, but what the fuck is wrong with saying 'reconfigure'? Is it because it's a word everyone understands and therefore you can't justify the 50 years you spent at university?
Even if the sheer processing capability could be duplicated, at a similar scale, with similar power requirements, with today's technologies there is still no true intelligence in the circuitry that is as flexible as the mind, which can make split-second decisions (good or bad) based on literally thousands of experiences and factors -- without requiring a "full data set" in order to arrive at the "best decision".
The best example I can think of is "a WTC tower is falling down, what do I do? Do I run? and how far? When do I try to turn a corner to escape the dust blast? Do I altruistically tackle the person in front of me because I can tell that the only way they can survive is if I cover them at peril of my own existence? What about UA Flight 93? or any of the other thousands and perhaps millions of heroic acts we know of from just 9/11?? How do you program or develop electronic logic like that? Into mobile, autonomous units capable of effective action?
Not in our lifetime, methinks.
...Open Source isn't the only answer -- but it's almost always a better value than the alternatives...
Emotion and Learning
Trust the Computer. The Computer is your friend.
did anyone else go all cross-eyed when they thought about the implications of running the turing test with one of these?
Is there an inverse Turing test?
Maybe we can make machines that fail it.
Keep your packets off my GNU/Girlfriend!
I am intrigued by his work in combining the top-down and bottom-up work with his "codelets" design which relies on probabalistic results from a bottom-up approach that are weighted and driven in a more top-down manner. This higher-level approach is meant to simulate "mind" rather than "brain", but I'm eager to see just how far towards "mind" the neural approach in the article can be taken.
[youmaynotcare]It's cool to see McCormick in an AI article. My first course from him was AI, and it fascinated me.[/youmaynotcare]
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Geez, surely we can do better! Most of the ones currently in production seem to be defective!!
(Get me that guy that figured out what was wrong with HAL...)
First it was the H-1B's taking our jobs, and now artificial brains. I should've been a dancer.
How many output bites?
MIT is already there.
Homer: "I- am- a- washing- machine... do- what- I- say..."
The quantitative description of cell structures in light microscope images is an important task in biological research. Quantitative measurements can be compared between different experiments which increases their usefulness to the biological research community.
Our research have indicated that replicating the human brain just will not work, actin and other things can't simply be reproduced into AI.
Digital imaging has made this task feasible because computers can now be programmed to automatically detect cell structures. Furthermore, the digital image analysis of cells has been improved by the use of fluorescent markers to tag specific structures simplifying the image segmentation problem.
Actin, a protein common in muscle cells of animals, forms fibers and fiber bundles which can be dyed with fluorescent markers and then detected by a light microscope. Quantitative measurement of the properties of Actin fibers will lead to a better understanding of how Actin interacts with other cell structures and contributes to cell locomotion and morphology.
We present a method for detection of Actin fibers in 2D images. Our approach has three stages.
First, a set of pixels that follow the contours of the fibers in the image is extracted from the original gray-scale cell image using edge detection techniques. Each fiber has two edges associated with it, so the next step eliminates one edge associated with each fiber by selecting an interval of edge direction such that one half of the edge pixels lie in this interval. The surviving edge pixels that have an edge magnitude above a threshold are selected and then thinned.
The second stage connects all of the edge pixels into a minimal spanning tree, using inter mediate algorithms from computational geometry. As a result, successive points from a fiber contour will tend to be linked. However, the tree will also connect points that belong to different fiber contours partly because the fibers intersect in the image, but also because by definition a tree must provide a path of links between any two vertices in the tree.
The third and final stage extracts the individual fiber contours from the minimal spanning tree. Long links within the tree are deleted because they connect two different fibers. Intersections of multiple fiber contour at a tree vertex are handled by heuristics based on proximity and on rough collinearity. The overall result is a set of fiber contours that appear in the a 2D cell image.
Our approach has worked well on a small set of real and synthetic images. The minimal spanning tree approach has proved fairly accurate because it groups pixels based on a global perspective rather than relying on uncertain local predictions of where fibers might extend.
These results are just way too bizarre, trust me, people have been trying to do this since the 60's!
It seems that this could be capable of showing if there's more than just the neurons involved.
"A language that doesn't affect the way you think about programming, is not worth knowing" - Alan Perlis
You will be able to buy a chia-pet, that's an order of magnitude smarter than you are, for the price of a gallon of milk.
And all these smart devices will be able to communicate with each other.
AI's bribing the government to forward their goals.
... has quoted the Orange Catholic Bible? "Thou shalt not make a machine in the likeness of a human mind."
I'm ashamed of you people.
Hey kids, there's only 5 days left 'til Yak Shaving Day!
If I'm feeding the troll, too bad; at least it's a philosophical one.
...
"which can make split-second decisions (good or bad) based on literally thousands of experiences and factors -- without requiring a "full data set" in order to arrive at the "best decision"."
That's an obvious contradiction in terms, isn't it?
"How do you program or develop electronic logic like that? Into mobile, autonomous units capable of effective action?"
Well, see, we've got these things called stored-program computers... =)
Do I have to finish that sentence, or do you see what I'm getting at?
You're awfully good at jumping up and down and telling us that you don't know the answer, but what's the point of that?
Anyway, is there some hidden meaning here I'm not getting?
oh yeah?