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Student Maps Brain to Image Search
StonyandCher writes to mention that a University of Ottawa grad student is creating a search engine for visual images that will be powered by a system mapped from the human brain. "Woodbeck said he has already created a prototype of the search engine based on his patent, which apes the way the brain processes visual information and tries to take advantage of currently-available graphics processing capabilities in PCs. 'The brain is very parallel. There's lots of things going on at once,' he said. 'Graphics processors are also very parallel, so it's a case of almost mapping the brain onto graphics processors, getting them to process visual information more effectively.'"
that is definitely interesting, but really, can such thing work? i don't think so.
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turn out like a bad nightmare after watching A clockwork Orange ??
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Reminds me of this article: Computer model behaves like humans on visual categorization task.
I worked in visual brain research for years, and can vouch there are lots of skeletons in the closet, or elephants in the drawing room: there is no accepted model of the statistics of real images (corners, occlusion, shading), nor of the algorithms necessary to infer them from inputs, nor of the learning process to infer those algorithms. Yes the brain is parallel, and yes it involves robust, fuzzy processing and analog values, but we not only don't know how the brain does it, we don't even know what problem it's trying to solve. The good news is that if this student does indeed have a business model and a real-world problem people will pay to solve, then the ratchet of engineering evolution could give us some real traction into understanding and solving this mystery. Good luck!
You might end up with a search engine that just looks for pr0n.
If a baby duck is a "duckling," why would anyone want to eat "dumplings?"
You still need to physically tell it somehow what you are looking for. How useful would it be?
best troll ever
Anybody else think image-in-results-out when they first read the summary? Actually, even TFA doesn't make this plainly obvious until you're decently through it.
Once I was past that, I thought it was pretty interesting. It could lead to more honest tagging of videos on YouTube, for example. No more keyword nonsense, just tags assigned by the engine.
This is a pretty useless article. Doesn't really tell how he's planning on doing it. It's a patent pending method. All it basically says is "Hey, look what we might be able to do". Even the quote from the expert doesn't do anything to tell me this problem is on its way to being solved.
Now that IS funny.
Now I'll have to find someplace else to hide my twisted fantasies.
This is my opinion. To make sure you don't steal it, it's covered by the DMCA.
What happens when you ask it to search for goatse?
Sadly, all that ever was found was porn.
..processors do one thing at a time, so they would be linear, not parallel.
it's impossible to tell if this guy is patenting the idea of doing vision on gpus (in which case there's prior art going back to before 2004 and probably even beyond that in the gpgpu community) or if he's talking about some tremendously clever collection of algorithms that happens to map well to gpu hardware. either way, i suspect that the poor guy is about to discover the hard way just how extraordinarily difficult this problem is.
Web search does not immediately reveal any details of his algorithm or any relevant papers, just media publicity. He does not even seem to have a web page.
light blain...
Yeh, there be parrallellism there....
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I have a bit of an issue with that statement. I guess in a way it is true that the brain does multiple things simultaneously such as balancing the body and chewing gum ;), but any article on multitasking will tend to point out that the brain isn't very good at processing higher functions simultaneously. I guess the main goal may not be to simultaneously process multiple images, but to quickly process a single image (which the brain is good at) based on the content rather than the meta-data associated with it.
If you can, the patent system is more than a little bit broken, though I guess we all know that by now. I would think that the existance of the brain would constitute prior art...
Crap article - and it sounds as if this fellow should put in a resume to Evolved Machines - http://www.evolvedmachines.com/
An Nvidia spot....*drum roll*....featuring neural simulations on GPUs
http://www.nvidia.com/object/tesla_testimonials.html
Music for coding. Genetic algorithm driven visuals. http://www
This isn't a terribly new idea. Just a lot of hype. Boy, I wish my Ph.D. dissertation work got Slashdotted!
While I was an intern at the Jet Propulsion Laboratory, back when I was an undergraduate, I was very gung-ho about biologically inspired computing - I implemented an automatic flowchart positioning system using a genetic algorithm that would "evolve" a correct solution to the problem. While this certainly worked to some extent, the instability and sheer unpredictable nature of using such a stochastic algorithm made it impossible to use in a mission-critical setting. Many biologically inspired algorithms solve problems through methods that cannot be proven correct (unlike, say, the mathematics circuitry in a CPU), but merely empirically observed to "do a good job."
One of the main drawbacks of human engineering is the need for certainty, which often prohibits the use of many high-efficiency stochastic algorithms (especially for things like mesh communication) in conservative industries, like the US defense industry. This is also a significant problem in other areas, however, and many biologically inspired algorithms have properties that we cannot, so far, completely explain - they are treated like "black boxes" with many unknowns for engineering purposes.
I think that in certain circles, the tremendous success that is evolution on this planet has overshadowed its inherent weaknesses - that it is a greedy, local optimizer which cannot reach a large amount of the possible biological search space due to being stuck in local optima, and the added constraint that everything must be constructed out of self-replicating units (these two factors are why something useful, like, say, a Colt 45, will never emerge without the pre-existence of an intelligence). Biological examples are fascinating and often practical, but the biological approach is almost always "brute force" and/or "sub-optimal but still alive."
I think biologically-inspired algorithms will continue to gain prominence, but in my estimation, it is likely that there will be harsh limits imposed on how far guarantees of performance from empirical tests and symbolic analysis will actually hold.
(Blatently pasted from my post a few years ago)
I'd imagine that the number of "Probable Hits" will be heavily weighted toward pr0n sites if anyone from around here gets mapped.
The problem with quotes on the internet, is that nobody bothers to check their veracity. -- Abraham Lincoln
There's prior art to mapping the brain onto electronic computing devices:
It was done in at least one episode of Star Trek.
And if future prior art published in the distant past is not suitable, then Wallace's cross human-rabbit brain mapping ("Wallace & Gromit - The Curse of the Were-Rabbit") might apply (a rabbit's brain IS a kind of electronic computing device, as is a human brain.
Both examples are both "prior" and "art"!
If not applicable, prepare to either pay a licensing fee or stop using your brain (if you haven't done so already). Perhaps legislators should prepare by creating a special tax and mandatory license. And the free culture community should devise alternatives that bypass the patent by accomplishing the same functionality without the usage of a brain (plants provide plenty of prior art to brainless existence, as do most inanimate objects.
Anyway, if such patents are accepted and legislators do not prepare in advance it might be quite difficult to invalidate it because the judges and jury would depend on the patented technology to do their job...
And the beer goggles strike again!
The above link Traumatic Images looks like is searches google for clockwork orange images when infact it goes to goatse, if firefox scrolled the URL then you would be able to see all of it any know that it goes to goatse but because it doesn't you can't tell where it goes.
This looks like a good one for some kind of attack (possible a goatse one)
thank God the internet isn't a human right.
I call BS on the article as well...
As far as "generic object recognition" goes, we are VERY far from a Holy Grail. State-of-the-art algorithms so far have a 45-55% successfull recognition rate, when dealing with only 101 objects categories (Caltech 101 database). Basically, with only 101 object to choose from, your "search engine" would get it wrong half the time. Not very useful if you ask me. Let alone with hundred of thousands of categories as he claims.
On top of that, the best and brightest are already working on this problem at MIT, in Dr. Poggio's lab (Computational Intelligence), who along with Marr, started the field of computer vision. The problems encountered are still at the theory level, not in the implementation. So a GPU implementation shouldn't change much.
disclaimer: i am also a graduate student working on the problem, who also happens to have graduated from the University of Ottawa
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