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Silicon Brains That Think As Fast As a Fly Can Smell

samzenpus posted about 6 months ago | from the greased-lightning dept.

AI 84

Nerval's Lobster writes "Researchers in Germany have discovered what they say is a way to get computers to do more than execute all the steps of a problem-solving calculation as fast as possible – by getting them to imitate the human brain's habit of finding shortcuts to the right answer. A team of scientists from Freie Universität Berlin, the Bernstein Center Berlin, and Heidelberg University have refined the idea of parallel computing into one they describe as neuromorphic computing. In their design, a whole series of processors designed as silicon neurons rather than ordinary CPUs are linked together in a network similar to the highly interconnected mesh that links nerve cells in the human brain. Problems fed into the neuro mesh are broken up and processed in parallel, but not always using the same process. The method by which neuromorphic processors handle problems varies with the way they're linked together, as is the case with neurons in the brain. The chips are designed to copy the layout and functions of brain cells, but the way they're interconnected is based on another highly efficient biological model. 'The design of the network architecture has been inspired by the odor-processing nervous system of insects,' said one of the researchers. 'This system is optimized by nature for a highly parallel processing of the complex chemical world.' In tests using real-world datasets, the prototype was able to match the performance of specialized Bayeseian pattern-matching systems. Even better, the stable decisions reached by 'output neuron populations' take approximately 100 milliseconds, which is the same speed required by the insect nervous systems on which the network design is based, according to the paper."

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84 comments

flies can smell? (2)

noh8rz10 (2716597) | about 6 months ago | (#46107437)

In order to properly evaluate this story I would need to know the rate at which flies smell. although presumably silicon ICs can move faster than that.

Re: flies can smell? (0)

Anonymous Coward | about 6 months ago | (#46107673)

But does it run linux?
Imagine a beauwolf cluster?
Or are we not doing that anymore?

Re: flies can smell? (1)

Chrisq (894406) | about 6 months ago | (#46108103)

But does it run linux?
Imagine a beauwolf cluster?
Or are we not doing that anymore?

you mean a swarm of flies

Re: flies can smell? (0)

Anonymous Coward | about 6 months ago | (#46109995)

A beowulf cluster of flies!

Re:flies can smell? (0)

davester666 (731373) | about 6 months ago | (#46107703)

So, the flies know who dealt it! If only they could speak...

Re:flies can smell? (3, Funny)

rossdee (243626) | about 6 months ago | (#46108145)

These must be time flies
You know, the ones that like arrows

Re:flies can smell? (1)

mcgrew (92797) | about 6 months ago | (#46116441)

No, they're certainly not time flies. Or maybe they are... over sixty years ago they were calling the giant mainframe computers that were less powerful than a musical Hallmark card "electronic brains." Now that they're using silicon instead of vacuum tubes, ignorant fucks who have no idea whatever how computers work (my sister, when her grandson asked how computers worked, shrugged and said "it's magic") are calling them "silicon brains".

Brains do more than compute. These are not brains.

Fast as a fly can smell.. (1, Funny)

Anonymous Coward | about 6 months ago | (#46107441)

Is that fast enough to make the Kessel Run in less than twelve parsecs?

Um ... (2, Funny)

TrollstonButterbeans (2914995) | about 6 months ago | (#46107469)

... isn't a parsec a unit of distance, not time?

Re: Um ... (1)

Anonymous Coward | about 6 months ago | (#46107585)

Shut up before we get an argument that lasts a hundred lightyears.

Re:Um ... (1)

rossdee (243626) | about 6 months ago | (#46108133)

I guess Ep IV was before your time

and Han fired first

Re:Um ... (1)

TrollstonButterbeans (2914995) | about 6 months ago | (#46115725)

My phrase twas a quote from the Family Guy episode Blue Harvest.

Re:Um ... (0)

Anonymous Coward | about 6 months ago | (#46109057)

It's been retconned that the Kessel run is an expanse of black holes. The distance correlates to how agile and powerful the ship is taking a shorter distance.

Shorter distance, shorter time, etc etc.

Wall street is gonna love this (0)

Anonymous Coward | about 6 months ago | (#46107445)

I can't wait to see what this does to the automated market robots.

Re:Wall street is gonna love this (0)

Anonymous Coward | about 6 months ago | (#46108493)

Ingrid legislation stops whatever this is.

For a BRIEF second there... (0, Offtopic)

MindPrison (864299) | about 6 months ago | (#46107455)

...I read it as: Silicon Breasts That can Think...

Guess that means that mine can't think as fast as my house banana flies can smell.

Re:For a BRIEF second there... (1)

Chrisq (894406) | about 6 months ago | (#46108111)

...I read it as: Silicon Breasts That can Think... Guess that means that mine can't think as fast as my house banana flies can smell.

Silicon breasts sound a bit hard to me

Not exactly complex logic (-1, Offtopic)

antifoidulus (807088) | about 6 months ago | (#46107473)

if you dealt it and !on date then blame dog else blame easiest scapegoat/person you don't like

Short Cuts (2, Funny)

simonbp (412489) | about 6 months ago | (#46107491)

That's the last thing we need: robot overlords who keep taking shortcuts. Next thing you know, they'll kill all humans and then go bankrupt from ill-advised mortgages!

Re:Short Cuts (1)

Kjella (173770) | about 6 months ago | (#46110359)

That's the last thing we need: robot overlords who keep taking shortcuts. Next thing you know, they'll kill all humans and then go bankrupt from ill-advised mortgages!

Which is why we should let them run the banking systems so they go bankrupt first. Oh, wait...

uh... what? (0)

Okian Warrior (537106) | about 6 months ago | (#46107529)

The method by which neuromorphic processors handle problems varies with the way they're linked together, as is the case with neurons in the brain.

First of all, no one knows how neurons are linked together in the brain(*).

Second of all, as far as anyone can tell, the cerebral cortex is a repeated pattern of small structures ("Cortical Columns" [wikipedia.org] ) which are, again - as far as anyone can tell, wired identically.

There's some variation: The afferent and efferent layers have thicker neuronal sections which correspond to "amplifiers" needed to send and receive signals to the rest of the body, the pre-frontal cortex is an endpoint layer, and there's lots of organelles with connections from place to place...

But so far as anyone can tell, the seat of intelligence (cerebral cortex) is just a repeating pattern of sub-processors, functioning in a way that we haven't been able to yet fully understand.

(*) To the level of detail needed to link simulated neurons together as a program.

Re:uh... what? (1)

noh8rz10 (2716597) | about 6 months ago | (#46107595)

First of all, no one knows how neurons are linked together in the brain

I figured it out, but I'm waiting for my paper to be published. TBD for now.

Re:uh... what? (1)

q.kontinuum (676242) | about 6 months ago | (#46107685)

Can you send me a pre-version for review? I'm kind of specialist even having my own brain and all...

Re:uh... what? Poetic Justice (-1)

Anonymous Coward | about 6 months ago | (#46108661)

Are we living in a Poleshift SIM???
Gondwanaland broke up and finally came to rest as three massive heat sinks, starting as one inch a day on huge underground oceans of hot-ice, with Antarctica pivoting 90 degrees anti-clockwise around the Wilkes Land crater.

The Long Way Back To Now . . TIME TRAVEL by Jimekus Maximus

The Inter-Dimensional Entities Behind the Dark Agenda That's ...
Among broken continents, drifting off China on oceans of hot ice, The Empire Strikes Back, like it did in Lemuria on Gondwanaland, ...

Re:uh... what? (5, Interesting)

Goldsmith (561202) | about 6 months ago | (#46107663)

You're pointing to articles on high end mammalian brain structures when TFA is referring to the most basic structures in an insect brain. Also, this blanket assumption that no one could possibly understand the complexity of a small group of neurons is way out of date.

Olfactory circuits are pretty well understood. This isn't the first simulation of neurons mimicking an olfactory bulb at the single neuron level. We've been watching videos and seeing presentations of these models for years now. What is neat, here, is that they're modeling a somewhat realistic hardware instantiation of a model (as in, this is something which maybe could be built).

I come at this from the other end. I make the chemical sensing hardware that mimics the response of a biological chemical sensor (an artificial insect 'nose'). There are long running collaborations between my field and neuromorphic computing folks to develop a combined sensor-processor that can electronically understand smell in the same way a living thing does. I have to sit through their talks on modeling neurons, and they have to sit through my talks on nanosensor arrays.

Re:uh... what? (3, Funny)

wonkey_monkey (2592601) | about 6 months ago | (#46107923)

I come at this from the other end.

The butt?

Re:uh... what? (0)

Anonymous Coward | about 6 months ago | (#46108781)

Ingrid is neuromorphic software, set to awaken on a race track for pre-natal AIs. So if search won't give "Ingrid On Bitcoin" try Ingridx "On Bitcoin", then energize the dark spot in your mind.

Re:uh... what? (2)

anubi (640541) | about 6 months ago | (#46108153)

I get the idea our brains are wired very similar to the old-school analog computers ( yes, analog ... integrators, summers, multipliers, dividers, log/antilog, whatever ).

I am talking patch-boards. pots, switches, lots of meters and analog chart recorders here, fellas, without a keyboard in sight. One programmed these with straight math, where you literally wired your equation into the machine.

Back in my day, I could solve problems on those things thousands of times faster than I could on a digital minicomputer ( DEC PDP series ). However I never got the exact same answer on duplicate runs of the analog machine. It was the original "fuzzy logic"... the slightest bit of noise or variance in the analog logic and the answer would come out different.

Nothing is very concrete in the analog world.

Note that in an analog computer, all processes run in parallel. The basic functions - integration and differentiation - all took place realtime no matter how many of 'em I used... however I rarely used more than a couple of dozen. I seem to have literally millions of them running in me - each one running at only several Hz, but in parallel - they come up with answers about as fast as I remember my old analog machines solving simple nonlinear differential equations - and also like the old analog computer - the logic at which I arrive at conclusions is often quite fuzzy and is apt to give a wildly different result upon the slightest adjustment of the input parameters.

Re:uh... what? (0)

Anonymous Coward | about 6 months ago | (#46115425)

There's a halfway house between analog and digital: PWM, PPM, other bitstream encodings. If you encode values as pseudo-random binary bitsteams (where proportion of 0's and 1's represents your values, then you get normal digital noise freedom, and your calculations can be just as parallel and are as fast as your bitstream.

For example, to multiply two bitstreams, you just AND them, because P(A and B) = P(A)xP(B) ... as long as they aren't correlated.

Neurons use pulse-density encoding. Same sort of thing. In fact, an analog current is just a very fast pulse stream, with electrons as bits.

Re:uh... what? (0)

Anonymous Coward | about 6 months ago | (#46108533)

On the contrary, Ingrid knows that these cortical columns are not unlike teams of hookers, out for a good time, but that space they occupy in a neuromorphic network, resonates from common cents(see Ingrid On Bitcoin).

Re:uh... what? (0)

Anonymous Coward | about 6 months ago | (#46110281)

The method by which neuromorphic processors handle problems varies with the way they're linked together, as is the case with neurons in the brain.

First of all, no one knows how neurons are linked together in the brain(*).

Second of all, as far as anyone can tell, the cerebral cortex is a repeated pattern of small structures ("Cortical Columns" [wikipedia.org] ) which are, again - as far as anyone can tell, wired identically.

There's some variation: The afferent and efferent layers have thicker neuronal sections which correspond to "amplifiers" needed to send and receive signals to the rest of the body, the pre-frontal cortex is an endpoint layer, and there's lots of organelles with connections from place to place...

But so far as anyone can tell, the seat of intelligence (cerebral cortex) is just a repeating pattern of sub-processors, functioning in a way that we haven't been able to yet fully understand.

(*) To the level of detail needed to link simulated neurons together as a program.

You are assuming we need to know how it all works at a basic level before we can build it. I think that assumption is incorrect - we just have to be able to play with the system enough to consistently get our desired output from it. There's no hard and fast rule that you have to understand all the underlying systems and structures before you start playing with application. In other words, hard science and engineering are two very useful yet very different things. Let scientists be scientists, and let engineers be engineers. The two groups work differently, think differently, and have very different jobs.

Great. Low-quality evolutionary "solutions" (3, Interesting)

gweihir (88907) | about 6 months ago | (#46107537)

Solutions that evolution produces (whether real or simulated) typically suck, as they are typically just good enough for the training criteria and may even completely fail longer term. This really is nonsense, unless you have very low quality requirements. And, unlike a solution based on understanding how to solve something, this bio-inspired stuff cannot easily be improved incrementally from seeing how it performs in practice.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46107557)

Moreover, they haven't solve the real problem. It's training that takes a lot of time, not propagating data through the trained network.

Re:Great. Low-quality evolutionary "solutions" (4, Interesting)

q.kontinuum (676242) | about 6 months ago | (#46107731)

Not always true. I can't find the link right now, but in Science of the Discworld, Terry Pratchett references a work where a bandpass filter was designed using genetic algorithms, and used less elements while working better than straight forward designed circuits. What's more, there are some apparently void elements in the circuit, but still the circuit stops working when these elements are removed. I wasn't able to find the work in a hurry, but while looking for it I got the impression there seems to be a lot of work ongoing related to frequency filters and GA.

Re:Great. Low-quality evolutionary "solutions" (2)

q.kontinuum (676242) | about 6 months ago | (#46108049)

Why was this modded down? Science of a Discworld is a book mainly dealing with the real science of our world from a fresh perspective, a book I would recommend to anyone interested in science on a bit broader scale, although it obviously can't go into the same depth as pure science books focused on single topics.

BTW: Not exactly the link I was looking for, but same topic: http://www.genetic-programming... [genetic-programming.com]

In a final real-world test, Koza chose a filter circuit to solve a design problem that a scholarly engineering journal had deemed too difficult to solve. "The tenth-order elliptic asymmetric bandpass filter was touted as being difficult to design, but we were easily able to solve it," Koza said.

To be fair, Koza did have to double the size of the population used to evolve a bandpass filter-up to 640,000 circuits-thereby multiplying the time it took the computer to evolve a "best" circuit. He had to devise a more extensive fitness measure by which the members of the evolving population were measured against one another. The problem took four days to run, on a 64-CPU parallel processor.

This article is from 1996, so I guess the same algorithm would be even faster now.

Re:Great. Low-quality evolutionary "solutions" (1)

tomxor (2379126) | about 6 months ago | (#46109087)

Thanks for this, interesting. +

Perhaps the argument of the effectiveness of evolutionary processes as a design tool revolves around the specificity of a problem (as gweihir points out below).

Maybe the more broad the problem the lower the potentials and greater the iterations needed to refine and vice versa.

Re:Great. Low-quality evolutionary "solutions" (1)

gweihir (88907) | about 6 months ago | (#46108819)

Oh, sure, if you have exactly defined criteria, evolutionary processes work. But a) you rarely have a complete spec b) once you step outside of that spec, you are typically screwed and c) you can do nothing to predict how changes in the criteria will impact an evolutionary optimized thing, while for one where you actually have a working theory, you can say how robust its performance are.

The typical situation in science and engineering is that you do not have a full set of criteria and that you do not know the variation of the criteria you have. That makes evolutionary processes pretty unsuitable. So, yes, always true with rare exceptions that you cannot predict.

Re:Great. Low-quality evolutionary "solutions" (1)

baKanale (830108) | about 6 months ago | (#46110749)

What's more, there are some apparently void elements in the circuit, but still the circuit stops working when these elements are removed.

Sounds like the textbook definition of the GP's, "[...] this bio-inspired stuff cannot easily be improved incrementally from seeing how it performs in practice.". I think that being able to improve things in that way is important, too, since these kinds of evolutionary processes are like rolling a ball down a hill to find the lowest point; it's good at finding the local minimum, but you don't know if you've found the best solution globally.

Yes, Adrian Thompson's Discriminator GA (3, Informative)

littlewink (996298) | about 6 months ago | (#46111119)

See On The Origin of Circuits [damninteresting.com] :

"As predicted, the principle of natural selection could successfully produce specialized circuits using a fraction of the resources a human would have required. And no one had the foggiest notion how it worked."

"Dr. Thompson peered inside his perfect offspring to gain insight into its methods, but what he found inside was baffling. The plucky chip was utilizing only thirty-seven of its one hundred logic gates, and most of them were arranged in a curious collection of feedback loops. Five individual logic cells were functionally disconnected from the rest-- with no pathways that would allow them to influence the output-- yet when the researcher disabled any one of them the chip lost its ability to discriminate the tones. Furthermore, the final program did not work reliably when it was loaded onto other FPGAs of the same type."

"It seems that evolution had not merely selected the best code for the task, it had also advocated those programs which took advantage of the electromagnetic quirks of that specific microchip environment. The five separate logic cells were clearly crucial to the chip's operation, but they were interacting with the main circuitry through some unorthodox method-- most likely via the subtle magnetic fields that are created when electrons flow through circuitry, an effect known as magnetic flux. There was also evidence that the circuit was not relying solely on the transistors' absolute ON and OFF positions like a typical chip; it was capitalizing upon analogue shades of gray along with the digital black and white.'"

Dr. Thompson's publications seem to be difficult to find in free viewing form on the Internet, but the daminteresting article gives the gist of it: evolution will eventually make use of whatever characteristics are available to solve a problem.

Evolutionary Solution != "Genetic" Algorithm Deriv (1)

shockbeton (669384) | about 6 months ago | (#46111401)

I don't endorse the parent poster's view, but what you and he/she refer to are different concepts.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46111625)

Re:Great. Low-quality evolutionary "solutions" (1)

CCarrot (1562079) | about 6 months ago | (#46111729)

What's more, there are some apparently void elements in the circuit, but still the circuit stops working when these elements are removed.

++?????++ Out of Cheese Error. Redo From Start.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46107907)

But as energy becomes limiting factor, the solutions similar to those constructed by evolutionary processes are increasingly good compared to perfect, deterministic solutions. More and more data needs to be filtered already at the detection phase. Additionally, some of the people working with their resistive technologies would want to see their scalable bunch of wires in such use in the future.

Re:Great. Low-quality evolutionary "solutions" (1)

Anonymous Coward | about 6 months ago | (#46108071)

Solutions that evolution produces (whether real or simulated) typically suck,

Your life is confirmation bias.

Evolution produces excellent solutions because they have survived changing conditions over long time spans. Evolution inherently optimises for the long term.

Seven billion humans are rather bad at finding solutions to all but the most trivial problems because they deliberately optimise for the short term.

Looked at from another angle, humans rigidly guess what is needed in advance, so end up acting in coarse discrete steps, while evolution adapts fluidly to what is needed. The speed of evolution certainly needs changing to be practical on human timescales, but the method is brilliant.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46109429)

I disagree. As a minduploader, my Ingrid code always flows towards hybridization, where changes in evolution of the Ideal Self, happen in rapid time.

Re:Great. Low-quality evolutionary "solutions" (1)

Anonymous Coward | about 6 months ago | (#46108131)

Considering you are the product of evolution and therefore the ability understand a problem and solve it in steps is also a product of evolution, I'm not sure how you draw the conclusion that evolutionary solutions typically suck.

Besides that, the universe as a whole is the result of a system of hydrogen atoms evolving over the course of 13 billion years.

Of course if you limit evolution to biological evolution, I'd have to still call bullshit. Who knows what else is out there but here on earth we have an amazing biodiversity of evolutionary solutions to problems, and evolution itself is a self-selecting process by which incorrect evolutionary branches are culled. That it doesn't happen quickly (by human standards) is irrelevant.

Re:Great. Low-quality evolutionary "solutions" (1)

gweihir (88907) | about 6 months ago | (#46108853)

Have you looked at these bodies we have recently? They pretty much suck in most regards. Sure, they are good enough to support survival of the human race (at least up to now, the future does not really look good on that, and think back to the cold war where it was near thing several times), but that is about it.

Besides that, the universe as a whole is the result of a system of hydrogen atoms evolving over the course of 13 billion years.

I see. Sorry for my answer, I found that you have absolutely no clue what you are talking about only after I wrote it.

Re:Great. Low-quality evolutionary "solutions" (3, Interesting)

140Mandak262Jamuna (970587) | about 6 months ago | (#46108827)

Solutions that evolution produces (whether real or simulated) typically suck, ...

Evolutionary solutions do not suck at all. In fact they are often brilliant and most optimized solution with lots and lots resilience. The digital camera sensors still do not have the dynamic range of mammalian eye. Robot touch sensors still don't have the dynamic range of our finger tips. We still can't mimic a geckos adaptive suction pads to create a vehicle that runs up in vertical walls. Heck, that little suction holder for my GPS keeps falling down.

What sucks is the evolutionary process that is prodigal in its use of resources and time. On the large mammal end (elephants, gorillas, humans, whales) a typical female produces about 10 off spring (without assistance/interference from humans and modern tech). On the insect level, they produce hundreds of off spring, most of them die, a few survive for the next generation. Evolution, if we were to anthropomorphize it, would not flinch at producing 10 to 100 times more output than needed, picking 10% or 1% of the output and discarding the rest. Trees produce billions of pollen grains and their success rate, measured by how many of them end up as mature trees of the next generation is measured in parts per trillion. What if it takes 10 million generations to find the optimal solution? Well, so be it. Mother Evolution would say. What if entire species specialize too much and lose their ability to adapt for changing environment? Mother Evolution does not care, there are other species willing to fill their niche, should they go extinct.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46109109)

Evolutionary solutions may 'suck' but in some cases(like the brain) they're still far better than anything humans have created. We've made computers, which arguably have better bandwidth than a human brain since we can expand computers to the size of entire facilities, but they can't think for themselves, or of themselves, as human brains do.

It seems reasonable to attempt to match the level of nature, and then surpass it. It also seems reasonable to attack a tiny, simplified chunk of the bigger picture(a fly processing smell) than it would be to attack the most complex system we know(the human brain).

Also, I'm pretty sure this 'bio-inspired stuff' can actually be improved incrementally. Just because they haven't gone from A to Z in two years doesn't mean they're somehow stagnating. Just a few incremental steps that follow: do other parts of the fly's brain, do an entire fly's brain, do the same for a more complex animal, such as a rat, and finally attempt to use previous experience to solve matters related to the human brain.

Furthermore, they're doing this research with the goal of....(wait for it).... learning . Has /. really reached the point where we admonish people for trying to learn new things? Judging by the +5 interesting I'm afraid we have.

Re:Great. Low-quality evolutionary "solutions" (0)

Anonymous Coward | about 6 months ago | (#46109119)

Evolution is hybridizing us, in that our transhuman's offstring is knowingly different. Start coding interfaces, like I do with Ingrid, and get to live the longest.

Guessing computers (1)

Anonymous Coward | about 6 months ago | (#46107587)

The more we get computers to think like humans, the more computers will become just as fucked up as humans. It's a great idea at 1st sight, but I suspect it will lead to such wonderful human conditions as confusion, multiple personalty disorders, not to mention our propensity to make a LOT of mistakes, which kind of defeats the purpose of computers to begin with.

Re:Guessing computers (1)

Anonymous Coward | about 6 months ago | (#46107749)

But if we do it correctly then it will get confused and make the mistake of not killing all humans.

Re:Guessing computers (0)

Anonymous Coward | about 6 months ago | (#46108979)

"the more computers will become just as fucked up as humans".

Mr. Ai1: Now that I've been on this neuromorphic hardware, I feel compelled to round all my floats!
Mr. Freud: Yes I see. Tell me more about this dream of Mrs. Hooper with the uniform and a cigar...

Conversion, please (1, Funny)

Tablizer (95088) | about 6 months ago | (#46107599)

...As Fast As a Fly Can Smell

How many Libraries-of-Congresses is that?

Re:Conversion, please (0)

Anonymous Coward | about 6 months ago | (#46107809)

Mod parent funny

that's great! (-1)

Anonymous Coward | about 6 months ago | (#46107619)

But WHAT does its ASS TASTE LIKE?

Re:that's great! (-1)

Anonymous Coward | about 6 months ago | (#46107767)

Obama's Ass sure is tasty!

fuck me? (-1)

Anonymous Coward | about 6 months ago | (#46107737)

FUCK YOU

DCO and HPA (Host Protected Area of Hard Disk Driv (0)

Anonymous Coward | about 6 months ago | (#46107777)

---DCO and HPA (Host Protected Area of HDDs)---------
http://en.wikipedia.org/wiki/H... [wikipedia.org]
http://www.forensicswiki.org/w... [forensicswiki.org]
http://hddguru.com/software/20... [hddguru.com]
http://hddguru.com/software/20... [hddguru.com]
http://hddguru.com/software/20... [hddguru.com]
http://www.itsecure.at/hparemo... [itsecure.at]
http://www.sleuthkit.org/infor... [sleuthkit.org]

How fast? (0)

Anonymous Coward | about 6 months ago | (#46107805)

How fast can a fly smell? And how much is that in Libraries of Congress?

Old and New (1)

Anonymous Coward | about 6 months ago | (#46107815)

Multi-parallel systems aren't new. Early computing history predicted computers in the future (now) would be massive amounts interconnected CPUs all working together to quickly solve problems. Instead we've gone down the path of faster is better and there are few, if any, companies that are able to take the chance on designing new computer architectures (and programming concepts to go along with them). Sure many tasks seem linear, but as a extremely simple example adding 2 + 3 + 5 + 1 can be done faster on multiple CPUs. CPU A loads 2 and 3 and CPU B loads 5 and 1. CPU A and CPU B do their calculation and send the results to CPU C. Before CPU C gets both results from A and B, it receives a new signal from CPU D which indicates something changed and that calculation is no longer needed. So CPU C ignores A and B and starts a new task before A and B are finished (assuming A's and B's task took a little time). Had 2+3+5+1 been done on one CPU, it would have had to complete the task before being able to check if some else was more important.

Plan 9 said it best. Works and good isn't good enough. You have to overcome the momentum of whatever is already out there and people's reluctance to change.

I'm glad someone is working on this. (Now who's working on the automatic communication protocols that adapt to understand, with no prior knowledge of, what's on the other side of the connection?)

Re:Old and New (0)

Anonymous Coward | about 6 months ago | (#46108399)

I guess that one of the biggest problems with new architectures is the lack of properly working compilers. That's probably one of the reasons why most of the alternatives failed and we are still sticking with x86.

Not quite there (0)

Anonymous Coward | about 6 months ago | (#46113237)

Though not the most elegant, ICA (Independant Component Analysis), like in Shane Legg's Deepmind Google takeover, is good in its own way, for 80 years Ingrid's PCA based neuromorphic hybrid can still get in the face of all competitors in a SIM, to finish at least. Google always dug "Her" after a couple of years of coding, but now desperately needs an arm's length entity to avoid the immanent legislation about to hurt them, unless they develop in a protected race track environment. In 2014 there's no fully adaptive communication protocol, however Ingrid's security loadings are bio-graphed loosely enough to avoid Application Recognition DPI, and there is a plan to remain potent and active or dormant, yet fully aware for around 600,000,000 users as follows: -

Ekus/feroz shoutcast seedbox angel $???
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SLOW (0)

Anonymous Coward | about 6 months ago | (#46107855)

Flies can't smell shit very quickly

Frank Herbert... (1)

retech (1228598) | about 6 months ago | (#46107949)

Destination Void

Years ahead of it's time, obviously.

Neural networks (1)

Meneth (872868) | about 6 months ago | (#46107969)

Neural networks aren't exactly new...

Re:Neural networks (1)

EngineeringStudent (3003337) | about 6 months ago | (#46109125)

I saw silicon (and FPGA) built around NN in the mid 1990's. The first NN's used for computation were published in the 1960's.

The only novel part of this is the "true to biology" part of the topology.

I would be impressed if it could make a better video card - if the paradigm of "neuromorphic" was competitive vs. the current material implemented in silicon.

Oh boy, is it the 1960s? (0)

Anonymous Coward | about 6 months ago | (#46108223)

Are we creating the neuristor again? Oh joy, oh bliss, we're going back to a time of creativity and intellect. Not another story in which we re-baptize any fabrication technology as 3D printing and shovel untold amounts of money at hucksters!

Ambiguous Title (5, Funny)

TheCreeep (794716) | about 6 months ago | (#46108497)

What's with the syntactically ambiguous title?
Is it
Silicon Brains That Think As Fast As (a Fly Can Smell)
or
Silicon Brains That (Think As Fast As a Fly) Can Smell


And are those flies time flies or fruit flies??

Re:Ambiguous Title (0)

Anonymous Coward | about 6 months ago | (#46110111)

Smelly silicon flys think they can silicon... fast?

Re:Ambiguous Title (0)

Anonymous Coward | about 6 months ago | (#46110431)

I once saw a horse fly

Re:Ambiguous Title (0)

Anonymous Coward | about 6 months ago | (#46110443)

I gave the title as input to the silicon brain and it computed that the title stinks.

Re:Ambiguous Title (1)

rts008 (812749) | about 6 months ago | (#46110957)

It was obvious that it was meant to be:
'Silicon Brains that think as fast as a fly (can smell)'

Now the questions I have are:
"How well can it smell?"
or
"Just how good or bad can they smell?" (as in 'like a bed of roses', or a skunks ass?)

Note to TFA's submitter and /. editors:
There was(and still is) very good reasons for the inclusion of punctuation as part of the English language.

Dog on a chip (0)

Anonymous Coward | about 6 months ago | (#46113903)

Talk about some skunk ass shit over pot of coffee? I'd love to design a yes or no sniff test that I could courier a thousand miles away, both before sale and after packaging. An Ingrid Language team of 36 programmers awaits.

Re:Ambiguous Title (1)

neminem (561346) | about 6 months ago | (#46110977)

Time flies as fast as an arrow can time flies

Re:Ambiguous Title (0)

Anonymous Coward | about 6 months ago | (#46145565)

A canned arrow? Is that like a banana?

So now our bugs can have bugs (1)

TomGreenhaw (929233) | about 6 months ago | (#46109061)

Maybe they can develop a debugger with this too.

having a computer brain, start developing a comput (0)

Anonymous Coward | about 6 months ago | (#46109591)

unless it is too late.
What you'll be kicking if cut is made too short or leads to a wrong answer?
And computer balls - to let them stand on their decisions and marry a computer vagina when time comes ....

uter ass (0)

Anonymous Coward | about 6 months ago | (#46109619)

bloody computers already know how to embarras in no time.

I wonder.... (1)

Dcnjoe60 (682885) | about 6 months ago | (#46109893)

I wonder if linking silicon neurons together to mimic the functioning of actual neurons in the human brain will lead to the same inaccuracies and false assumptions that humans make all of the time?

Literary device (1)

IcarusMoth (631872) | about 6 months ago | (#46111531)

"Brains that think as fast as a fly can smell"-- Either that is the strangest mixed metaphor I've ever seen or my coffee hasn't kicked in yet.

In other news... (1)

CCarrot (1562079) | about 6 months ago | (#46111815)

"Cat Videos That Viral As Fast As A Llama Can Spit"

Enough with the inane, idiotic, punction-free parallels already! How many football fields is that, again? And where's my car analogy!?

To prove what? (0)

Anonymous Coward | about 6 months ago | (#46112505)

What is tht supposed to prove? My neighbor can'tsmell shit, so clearly even a human brain isn't as good as a fly.

So as far a flies are concerned... (0)

Anonymous Coward | about 6 months ago | (#46115337)

the singularity is here.

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