Building Brainlike Computers

newtronic clues us to an article in IEEE Spectrum by Jeff Hawkins (founder of Palm Computing), titled Why can't a computer be more like a brain? Hawkins brings us up to date with his latest endeavor, Numenta. He covers progress since his book On Intelligence and gives details on Hierarchical Temporal Memory (HTM), which is a platform for simulating neocortical activity. Programming HTMs is different — you essentially feed them sensory data. Numenta has created a framework and tools, free in a "research release," that allow anyone to build and program HTMs.

End of civilization

[by Anonymous Coward]

Because it would signal the end of civilization...if computers can look like women (porn), feel like women (Realdolls), and think like women (have a brain, at least in some cases), then all procreation would cease and humans would suffer the same fate as the dinosaurs.

Re:End of civilization

[morari (1080535)]

Mystery solved! Dinosaurs went extinct because they developed super-sexy "DinoBots" and thus became disinterested in actual sex...

Re:End of civilization

[Bluesman (104513)]

Careful . . . I don't think you want your super sexy real doll to think like an actual woman.

That is, unless you want your old doll to get jealous of the new one and steal half your money and burn your house down.

How long before...

[alberion (1086629)]

...comps get lazy and start reading /. instead of working?

Interesting, but...

[Bob Hearn (61879)]

Hawkins' book On Intelligence is interesting reading. There are a lot of good ideas in there. From my perspective as an AI / neuroscience researcher, the main weakness in his approach is that he only thinks about the cortex, whereas many other brain structures, notably the basal ganglia, are increasingly becoming implicated as having a fundamental role in intelligence.

This quote from the article is telling:

HTM is not a model of a full brain or even the entire neo-cortex. Our system doesn't have desires, motives, or intentions of any kind. Indeed, we do not even want to make machines that are humanlike. Rather, we want to exploit a mechanism that we believe to underlie much of human thought and perception. This operating principle can be applied to many problems of pattern recognition, pattern discovery, prediction and, ultimately, robotics. But striving to build machines that pass the Turing Test is not our mission.

Well, my goal is to build machines that pass the Turing Test, so I have to think about more than cortex. But more generally, one might wonder how much of intelligence it is possible to capture with a system that "doesn't have desires, motives, or intentions of any kind".

Re:Interesting, but...

[CogDissident (951207)]

He means it doesn't have desires and motives in a conventional sense. The way it works mathamatically means that it seeks the lowest value (or highest, depending on the AI) for the next nodal jump, and finds a path that leads to the most likely solution.

This could be "converted" to traditional desires, meaning that if you taught it to find the most attractive woman, and gave it ranked values based on body features and what features are considered attractive in conjunction, it would "have" the "desire" to find the most beautiful woman in any given group.

I'd say that researchers need to learn to put things into layman's terms, but all we need are good editors to put it into simpler terms, really.

Off-Topic

[oringo (848629)]

Please take your professional/scientific reviews to real scientific journals. Only bitter/ignorant jokes are acceptable on /.

Re:Interesting, but...

[Bob Hearn (61879)]

Yes, that's a big part of it. The basal ganliga form a giant reinforcement-learning system in the brain. Cortex on its own can perhaps learn to build hierarchical representations of sensory data, as Hawkins argues. But it can't learn how to perform actions that achieve goals without the basal ganglia. And in fact, there is a lot of evidence that suggests that sensory representation are refined and developed based on what is relevant to the brain's behavioal goals -- that the cortico-basal-ganglia loop contributes to sensory representation as well as motor, planning, intention, etc.

Can't build what you don't understand

[sycodon (149926)]

Since they (scientists) don't really have a full understanding about how the brain works then it seems to me that building a computer to work like one is a litle far fetched.

Alchemy

[Weaselmancer (533834)]

Medievals didn't understand the atom or crystalline structures, but they still made carbonized steel for armour. They had the wrong ideas about exactly how metal became properly carbonized and tempered, but they still came up with correctly tempered spring-like steels (IIRC similar to tempered 1050) without getting any of the "why" of it right.

I think someday we will be viewed as the medievals of AI. We occasionally make progress even though we really don't know what we're doing. Yet.

a "full understanding" isn't necessary

[Bearpaw (13080)]

Hawkin's isn't trying to build a computer that works like a brain, anymore than the Wright brothers tried to build a plane that flew like a bird. They didn't need to "fully understand" how birds fly to get off the ground. All they needed was enough understanding to take what they could use -- wings, for instance -- and adapt it to an approach that didn't require feathers, hollow bones, and so on.

Hawkins and the people he's working with have come up with an approach that lets people explore possible uses of allowing a machine to learn in a way that's inspired by a process that may be part of how humans learn. They don't need a "full understanding" of how the human brain works to do that.

Recognition Is a Small Part of the Problem

[MOBE2001 (263700)]

Because of the neocortex's uniform structure, neuro-scientists have long suspected that all its parts work on a common algorithm-that is, that the brain hears, sees, understands language, and even plays chess with a single, flexible tool. Much experimental evidence supports the idea that the neocortex is such a general-purpose learning machine. What it learns and what it can do are determined by the size of the neocortical sheet, what senses the sheet is connected to, and what experiences it is trained on. HTM is a theory of the neocortical algorithm.

While I believe that the HTM is indeed a giant leap in AI (although I disagree with Numenta's Bayesian approach), I cannot help thinking that Hawkins is only addressing a small subset of intelligence. The neocortex is essentially a recognition machine but there is a lot more to brain and behavior than recognition. What is Hawkins' take on things like behavior selection, short and long-term memory, motor sequencing, motor coordination, attention, motivation, etc...?

Re:

[yali (209015)]

Much experimental evidence supports the idea that the neocortex is such a general-purpose learning machine.

I don't think that is anywhere close to representing the scientific consensus. A lot of scientists believe that the brain is specially adapted to solving specific problems [ucsb.edu] that were important for our ancestors' survival. For example, humans seem to solve logic problems involving social exchange [ucsb.edu] in very different ways, and using different neural circuitry, than problems that have the same formal-logic

What mistakes do machine learning machines make?

[totierne (56891)]

I take drugs for bipolar tendency and have had 5 nervous breakdowns, so I have some ideas about how the brain goes wrong, I am afraid that the search for a perfect machine learning device may be a side track compared to explaining the mistakes the brain makes.

I have an engineering degree and a masters specialising in machine learning - but that was 13 years ago, I would be delighted in more pointers of the state of the art

http://www.cnbc.cmu.edu/Resources/disordermodels/ [cmu.edu] , on bipolar and neural networks, seemed promising at one stage but I had not the time, energy or rights to read the latest papers. [The web page is dated 1996]

Re:this is stupid

[cyphercell (843398)]

Next you'll say that we're incapable of growing ears on rats right?

Re:this is stupid

[DragonWriter (970822)]

I'm just saying that the human brain is a thing made by god, and we can't copy it.

How does that follow? Granting, for the sake of discussion, that everything in the natural universe, including brains, was created by God, that hardly implies that we can't copy brains. We can reproduce many naturally occurring things, after all, through understanding their structure and composition.

Diamonds are things made by God, and we can copy them.

Re:this is stupid

[hackstraw (262471)]

Diamonds are things made by God, and we can copy them.

Regardless of there being a God, brains, humans, birds, or diamonds, to be honest we don't want to create a brainlike computer.

Human brains can do amazing things, but one thing we like about computers over human brains is that human brains, even the best ones, are simply wrong from time to time, and our goal with "brainlike computers" is not to recreate these mistakes, but rather to overcome them.

With respect to our senses, again, they are amazing, but then again they are fooled much of the time. There are perceptual errors, optical illusions, selective memories (ask 10 eye witnesses and get 10 different accounts), and all of that.

Today, computers are great at being calculators, and for storing and retrieving digital data. They suck at making "decisions". Even seemingly trivial ones like telling the difference between an apple and an orange is difficult for a computer today.

Take a look at much more mature technologies, like flying. For ages, humans tried to make flying machines like birds, and now we have a handful of flying technologies that can fly faster than the speed of sound and can go beyond the earth's atmosphere. But we still can't fly like a bird with flapping wings, and I don't remember a time in my life where I saw a headline saying "Building Birdlike Planes".

Re:

[DragonWriter (970822)]

Regardless of there being a God, brains, humans, birds, or diamonds, to be honest we don't want to create a brainlike computer.

Human brains can do amazing things, but one thing we like about computers over human brains is that human brains, even the best ones, are simply wrong from time to time, and our goal with "brainlike computers" is not to recreate these mistakes, but rather to overcome them.

The thing is, computers can already do lots of things that brains are bad at. Making brainlike software that all

Re:

[cyphercell (843398)]

http://www.transhumanist.com/volume1/moravec.htm [transhumanist.com]

Ok, according to moore's law we will get there, with a transistor based computer. I believe the idea is to create the hardware equivelant of a neuron. Something like Asimov's positronic brain. Currently the modern computer is little more than a highly programmable calculator. The idea in this case is to create a computer that can learn or repurpose it's transistors/neurons.

My colleagues and I have been pursuing that approach for several years. We've focused on the brain's neocortex, and we have made significant progress in understanding how it works. We call our theory, for reasons that I will explain shortly, Hierarchical Temporal Memory, or HTM. We have created a software platform that allows anyone to build HTMs for experimentation and deployment. You don't program an HTM as you would a computer; rather you configure it with software tools, then train it by exposing it to sensory data.

The end goal is to create more advanced computers or software. You'd do better vent

Re:this is stupid

[Bloke down the pub (861787)]

I'm just saying that the human brain is a thing made by god

In atheist Russia, God is made by the human brain!!!!

Actually, computer brains will be far superior

[Morgaine (4316)]

I know that you're merely trolling and don't actually believe what you say. Nevertheless ...

It's worth stating that unless you believe that the human brain contains magic (which 99% of your religious bretheren don't), then it is no more than a very complex arrangement of perfectly ordinary physical components, namely atoms and molecules. And if you don't think that we will in due course be able to arrange atoms and molecules as we wish, then you're very blinkered to the direction in which science and engineering are heading.

That said, the recreation of human brains is merely an interesting challange as far as practical engineers are concerned, and not a practical approach. The vast majority of us have no intention of actually taking that route because protein is such an inferior building material. Your alleged god (aka. blind evolution) only "chose" it because carbon is so damn versatile in conjunction with O and N and H, so a million different reactions occurred in the mess of the primordial soup. And one of them happened to work.

Well we don't rely on blind chance, but coerce the reactions in the direction we want, which gives us the chance to choose our materials more strategically. And we will.

There's not a chance in hell (trying to use your frame of reference here) of us producing "brains" that are *MERELY* as good as nature created in humans, because the equations that underpin ordinary physics and chemistry (and therefore molecular nanotechnology) say otherwise. Instead, you can expect "brains" a billion times our mental capacity and a trillion times our mental speed in due course. We know that it's possible (from theory, and by observing protein nanomachines doing it very poorly), but we lack the infrastructure to do it ourselves at present. It's many decades away, but hey, we're working on it. :-)

You'd have to contradict the maths and physics of materials and biotech that says that MNT is possible before you can validly say that it's not. And with the intellectual depth of your contribution above, my guess is that you won't. :-)

Re:

[operagost (62405)]

You did a very good job discrediting yourself with that last paragraph.

Re:

[kripkenstein (913150)]

It's all been done before, perceptrons, multi-layered perceptrons, recurrent connections, etc, etc, etc...dunno why anybody would pay attention

Well, yes and no. I think both you and the Numenta people are wrong about this (them saying that the failing of AI is that it ignores the brain). Here is my brief take on the history of AI and machine learning:

First, AI ignored the brain. Then, Neural Networks took off in the 80's, and during the 90's were also the 'hot thing' in AI and machine learning. Basical

Re: been there, done that...

[Black Parrot (19622)]

However, in the very specific field of machine learning, virtually all papers published are about support vector machines and similar methods

Sorry, but that is simply wrong. No, laughably wrong.

Browse the ToCs of some recent journals and conference proceedings on ML, RL, EC, NN.

Re:

[simm1701 (835424)]

Still based on birds though.

early jumpbo jets used the landings of pigeons as a basis for example - those techniques are still used