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Mapping The Brain To Build Better Machines (quantamagazine.org)
An anonymous reader quotes a report from Quanta Magazine: An ambitious new program, funded by the federal government's intelligence arm, aims to bring artificial intelligence more in line with our own mental powers. Three teams composed of neuroscientists and computer scientists will attempt to figure out how the brain performs these feats of visual identification, then make machines that do the same. "Today's machine learning fails where humans excel," said Jacob Vogelstein, who heads the program at the Intelligence Advanced Research Projects Activity (IARPA). "We want to revolutionize machine learning by reverse engineering the algorithms and computations of the brain." By the end of the five-year IARPA project, dubbed Machine Intelligence from Cortical Networks (Microns), researchers aim to map a cubic millimeter of cortex. That tiny portion houses about 100,000 neurons, 3 to 15 million neuronal connections, or synapses, and enough neural wiring to span the width of Manhattan, were it all untangled and laid end-to-end.
Stay away from the right parietal lobe...
“He’s not deformed, he’s just drunk!”
This cargo-cult approach to AI is ridiculous. Decades of effort have produced absolutely no result. Oh, but this time we're way smarter and better informed, surely we'll produce something of value this time. Gimme the grant monies, plz.
Oh, but this one is worse. It's not that gigantic failure. The laughable failure they're repeating this time is far, far, older: "We want to revolutionize machine learning by reverse engineering the algorithms and computations of the brain."
Computationalism?! Seriously? Not only is that laughable, it's been laughable for ages! Don't think so? People have been born and died of old age waiting for that bit of fiction to produce any results. So far? Nothing. On top of it all, there's more than one good reason to suspect it's never going to produce any results.
Let's base one retarded idea on another retarded idea and mix in a bunch of childish thinking about the function of the brain based on zero evidence. AI breakthrough!
I did a double-take at that -- it just didn't sound plausible. But, sure enough, Manhattan is just a couple of kilometers wide, and a kilometer is a million millimeters. If there are millions of axons passing through that cubic millimeter of cortex, that's about how far the segments would stretch in total.
You don't know what Moore's Law means. You need to stop using it in your writing.
Shutting down free speech with violence isn't fighting fascism. It IS fascism!
There's a better way to do it, and it could potentially image the whole brain, all at once. It can image whole brains of mice and other smaller mammals at the neuronal level, and we can tag each type of brain cell automatically.
Once you've got the raw data a simple AI program could map the structure logically by recognizing the tracers and plotting the connections...
Of course, this cheap and simple method may not put money in the right pockets. See what I'm thinking?
but trying to make computers act more like brains is just not a sound scientific concept.
You may not think it's useful, but there's nothing unscientific or unsound about it. It's a matter of understanding how the brain works, and throwing enough hardware at it to duplicate the essential operations.
You will need to make it out of nerve cells and glia then, because silicon won't cut it.
Just like air planes need to be made from bone, muscle and feathers, because otherwise they won't fly ? Seriously, what's so special about nerve cells that we can't duplicate on a functional level ? And how do you know that to be true ?
Because there are far too many things happening at too small a scale to even measure, let alone imitate. The unknowns in neurosicence far outnumber the knowns.
Take an intel Core i7 in a time machine, and drop it on someone's desk in the 60's. Ask him to imitate it. You'll probably get the same reply.
You can model certain brain functions with software to see what happens if you alter inputs to a neural circuit, but it will only be as good as weather predictions done in silicon.
Irrelevant. The reason we can't do good weather predictions is because weather is chaotic by nature.
And what makes you think that weather is more chaotic than neural activity?
Even if neural activity is chaotic, that only means we can't perform the same thing as a brain with 100% accuracy. But that's okay, because it also means that your own brain can never perform the same task again with 100% accuracy, and that is rarely a problem.
You can't imitate something that you don't understand. Understand?
That's not true. See genetic algorithms for instance.
That is not making an artificial bird, that is making a plane that flies people around. They are not even slightly the same.
The goal of a plane is to fly. The goal was never to mimic a bird. Similarly, the goal is to make a computer that can do tasks that our brain can do, but we don't have to make it run on ham sandwiches and milk.
Like I said, good luck. People have been trying for decades, and haven't gotten anywhere near emulating brain activity in silico.
Except for the ANN that just won a Go tournament. Or the ANNs that can do face recognition, speech recognition, or many other things.
Of course, they can't do everything that a brain can do, but a baby can't run a marathon either.
Deep learning based on sigmoidal belief nets is inspired by the architecture of the brain. Autoencoders are very similar in function to the "mirroring" that occurs in the brain. Silico and vivo are not as different as you believe.
I completely understand that non-biologists, who don't understand biological complexity, can think that making an artificial brain is quite doable.
I remember chess grandmasters arguing in the 80's that chess computers would never be able to beat them, unless they found a way to understand how a grandmaster plays, and somehow put that in code. Botvinnik wrote a book in 1984 about how computer programs should formulate long term plans. Now, with modern computer hardware, an expert programmer could write a chess program that would beat those grandmasters, while himself not possessing any more chess knowledge than can be picked up from a beginner's book. It shows that experts in a certain field may not be the best equipped to think outside their box.