The Cat is out of the Bag

[phongn]

Portland, OR - 18 Nov 2009: Today at SC 09, the supercomputing conference, IBM (NYSE: IBM) announced significant progress toward creating a computer system that simulates and emulates the brain’s abilities for sensation, perception, action, interaction and cognition, while rivaling the brain’s low power and energy consumption and compact size.

The cognitive computing team, led by IBM Research, has achieved significant advances in large-scale cortical simulation and a new algorithm that synthesizes neurological data -- two major milestones that indicate the feasibility of building a cognitive computing chip.

BlueMatter, a new algorithm created in collaboration with Stanford University, exploits the Blue Gene supercomputing architecture in order to noninvasively measure and map the connections between all cortical and sub-cortical locations within the human brain using magnetic resonance diffusion weighted imaging. Mapping the wiring diagram of the brain is crucial to untangling its vast communication network and understanding how it represents and processes information.

Scientists, at IBM Research - Almaden, in collaboration with colleagues from Lawrence Berkeley National Lab, have performed the first near real-time cortical simulation of the brain that exceeds the scale of a cat cortex and contains 1 billion spiking neurons and 10 trillion individual learning synapses.

(continues)

See paper here - in summary, IBM has simulated a brain more complex than a cat's on LLNL's Blue Gene/P

[Gilthan]

a computer system that simulates and emulates the brain’s abilities

Emulates is a bit of a strong word for this degree of a simulation, as, reading through the paper, there's no real decision-making or other functional thought demonstrated, not so much as being able to control a robot finding its way through mazes and learning. Without any real input resulting in any real output, without any comparison of the output to that which would result from a real brain, there's a lack of a metric for judging how closely (or not) the simulated neurons approach a brain in operation. More impressive would be a fully functional emulation of a brain that caused a robot in the real world to be able to act with so much as the intelligence of a young mouse, or, frankly, even just managing that at the level of an insect before shooting for the stars. Still, this is interesting.

[Simon_Jester]

I'm not sure I understand. To me, it sounds like they built a system with the computational complexity of a brain, at least an animal brain, but don't know what kind of software to put on it to get it to make decisions.

Is that right?

[Ace Pace]

A more understand perspective from Ars technica

An interdisciplinary team of researchers at IBM have presented at paper at the SC09 supercomputing conference describing a milestone in cognitive computing: the group's massively parallel cortical simulator, C2, now has the ability to simulate a brain with about 4.5 percent the cerebral cortex capacity of a human brain, and significantly more brain capacity than a cat.

No, this isn't yet another example of Kurzweil-style guesstimating about how many "terabytes" of storage a human brain has. Rather, the authors quantify brain capacity in terms of numbers of neurons and synapses. The simulator, which runs on the Dawn Blue Gene /P supercomputer with 147,456 CPUs and 144TB of main memory, simulates the activity of 1.617 billion neurons connected in a network of 8.87 trillion synapses. The model doesn't yet run at real time, but it does simulate a number of aspects of real-world neuronal interactions, and the neurons are organized with the same kinds of groupings and specializations as a mammalian cortex. In other words, this is a virtual mammalian brain (or at least part of one) inside a computer, and the simulation is good enough that the team is already starting to bump up against some of the philosophical issues raised about such models by cognitive scientists over the past decades.

In a nutshell, when a simulation of a complex phenomenon (brains, weather systems) reaches a certain level of fidelity, it becomes just as difficult to figure out what's actually going on in the model—how it's organized, or how it will respond to a set of inputs—as it is to answer the same questions about a live version of the phenomenon that the simulation is modeling. So building a highly accurate simulation of a complex, nondeterministic system doesn't mean that you'll immediately understand how that system works—it just means that instead of having one thing you don't understand (at whatever level of abstraction), you now have two things you don't understand: the real system, and a simulation of the system that has all of the complexities of the original plus an additional layer of complexity associated with the models implementation in hardware and software.

The more faithful the simulation gets, the bigger an issue this becomes. The researchers allude to it in section 3.2.2 of the paper, when they describe a measurement tool they call the "BrainCam."

"When combined with the mammalian-scale models now possible with C2," they write, "the flood of data can be overwhelming from a computational (for example, the total amount of data can be many terabytes) and human perspective (the visualization of the data can be too large or too detailed)."

The problem described above doesn't mean that accurate simulations are worthless, however. You can poke, prod, and dissect a brain simulation without any of the ethical or logistical challenges that arise from doing similar work on a real brain. The IBM researchers endowed the model with checkpoint-based state-saving capabilities, so that the simulation can be rewound to certain states and then moved forward again under different conditions. They also have the facility for generating MPG movies of different aspects of the virtual brain in operation, movies that you could also generate by measuring an animal's brain but at much lower resolutions. There's even a virtual EKG, which lets the researchers validate the model by comparing it to EKGs from real brains.

In the end, C2 is like having a (sorta) real cortex that you don't fully understand, but that you can rewind, snap pictures of, and generally measure under different conditions so that you can do experiments on it that wouldn't be possible (or ethical) with real brains.

Scaling and the singularity

One of the major results from the paper is that C2 exhibits "weak scaling." In other words, as the total amount of memory in the model scales, the number of neurons and synapses that can be simulated scales roughly linearly, also. This is important, because it means that a future version of Blue Gene with two or three orders of magnitude more memory (and associated bandwidth and processing power) will be able to simulate an entire human brain.

The model also exhibits "strong scaling," which means that increases in the amount of memory per CPU enable them to run the model faster, so that it will eventually be able to simulate a cortex in real time.

[Companion Cube]

A bit of comment from Henry Markram, the director of the Blue Brain project.

Dear Bernie,

You told me you would string this guy up by the toes the last time Mohda made his stupid statement about simulating the mouse's brain.

I thought that having gone through Blue Brain so carefully, journalists would be able to recognize that what IBM reported is a scam - no where near a cat-scale brain simulation, but somehow they are totally deceived by these incredible statements.

I am absolutely shocked at this announcement. Not because it is any kind of technical feat, but because of the mass deception of the public.

1. These are point neurons (missing 99.999% of the brain; no branches; no detailed ion channels; the simplest possible equation you can imagine to simulate a neuron, totally trivial synapses; and using the STDP learning rule I discovered in this way is also is a joke).

2. All these kinds of simulations are trivial and have been around for decades - simply called artificial neural network (ANN) simulations. We even stooped to doing these kinds of simulations as bench mark tests 4 years ago with 10's of millions of such points before we bought the Blue Gene/L. If we (or anyone else) wanted to we could easily do this for a billion "points", but we would certainly not call it a cat-scale simulation. It is really no big deal to simulate a billion points interacting if you have a big enough computer. The only step here is that they have at their disposal a big computer. For a grown up "researcher" to get excited because one can simulate billions of points interacting is ludicrous.

3. It is not even an innovation in simulation technology. You don't need any special "C2 simulator", this is just a hoax and a PR stunt. Most neural network simulators for parallel machines can can do this today. Nest, pNeuron, SPIKE, CSIM, etc, etc. all of them can do this! We could do the same simulation immediately, this very second by just loading up some network of points on such a machine, but it would just be a complete waste of time - and again, I would consider it shameful and unethical to call it a cat simulation.

4. This is light years away from a cat brain, not even close to an ants brain in complexity. It is highly unethical of Mohda to mislead the public in making people believe they have actually simulated a cat's brain. Absolutely shocking.

5. There is no qualified neuroscientist on the planet that would agree that this is even close to a cat's brain. I see he did not stop making such stupid statements after they claimed they simulated a mouse's brain.

6. You should also ask Mohda where he got the notion of "reverse engineering" from, when he does not even know what it means - look the the models - this has nothing to do with reverse engineering. And mouse, rat, cat, primate, human - ask him where he took that from? Simply a PR stunt here to ride on Blue Brain.

That IBM and DARPA would support such deceptive announcements is even more shocking.

That the Bell prize would be awarded for such nonsense is beyond belief. I never realized that such trivial and unethical behavior would actually be rewarded. I would have expected an ethics committee to string this guy up by the toes.

I suppose it is up to me to let the "cat out of the bag" about this outright deception of the public.

Competition is great, but this is a disgrace and extremely harmful to the field. Obviously Mohda would like to claim he simulated the Human brain next - I really hope someone does some scientific and ethical checking up on this guy.

All the best,

Henry

[The Duchess of Zeon]

A... *rubs head* Who the hell is telling the truth, then?

[Companion Cube]

It's way over my head, anyway! There's further comment from the Blue Brain guy, where he's commenting on a tech blog here (scroll down to the comments). His main objections are that the neurones in the cat brain simulation just don't reflect the behaviour of the real thing.

Not going to quote the whole thing since it's quite lengthy and this thread already consists mostly of huge quoteboxes.

They use an alpha function (up fast down slow) to simulate a synaptic event. This is a completely inaccurate representation of a synapse. There are at least 6 types of synapses that are highly non-linear in their transmission (i.e. that transform inputs and not only transmit inputs). In fact you would need a 10's of thousands of differential equations to simulate one synapse.

This is a bit surprising to me, since in a naive way I had assumed you could get away with just abstracting a brain simulation to the level of the individual neurones, rather than bothering with all of the molecular stuff happening inside. But then, I suppose to ignore the lower levels of detail you'd need a set of rules-of-thumb regarding how a particular neurone in a particular group responds to every different sort of input it recieves, and how the surrounding glial cells are involved in any of its synapses.

[Singular Intellect]

Damnit, where's Starglider and his confirmation this is the first step towards our technological singularity destiny?

Seriously though, this sounds very interesting, but somewhat deceptive with it's initial impression.

[Sarevok]

Is it not unethical to simulate a cat brain to perform research ? Now I know this is an early breakthrough on what remains a long uncharted road. But the argument that brain simulation will allow medical research to be performed that can not be done on live subjects seems pretty dodgy to me. If you are simulating a realistic cat that cat is no different than a biological cat. That makes me a bit upset knowing a virtual kitty is going to die someday.

[Gilthan]

I thought that having gone through Blue Brain so carefully, journalists would be able to recognize that what IBM reported is a scam - no where near a cat-scale brain simulation, but somehow they are totally deceived by these incredible statements.

I am absolutely shocked at this announcement. Not because it is any kind of technical feat, but because of the mass deception of the public.

1. These are point neurons (missing 99.999% of the brain; no branches; no detailed ion channels; the simplest possible equation you can imagine to simulate a neuron, totally trivial synapses; and using the STDP learning rule I discovered in this way is also is a joke).

Ah, a good description. I knew it wasn't even close to a real emulation, as their simulation wasn't doing any functional thought, not able to handle actual input streams and give useful output, not making decisions like a cat's brain would do so. Real cat brains are astronomically complex, down to all the details like various chemical messengers, trillions of synapses, etc.

An analogy for what is going on here:

Anything from a kid's simple crayon drawing to countless megabytes of blueprints with CAD files could be called a representation of an automobile, but not all representations are equal. Likewise, not all "simulations" are equal.

When true, functional simulation of complex brains occurs, it will be a group which rather follows the cardinal problem-solving rule for any "mission impossible" task: Break the great challenge down into smaller steps and successfully, verifiably manage each step before proceeding to the next.

When there's a group who first fully simulates small numbers of neurons and then a worm's brain or an insect's brain, gets such working so well that it responds to incoming signals with the same decision-making as the real brain, and has it even able to control a robot in the real world, then, in contrast, things would be looking up for doing so on progressively higher order brains and incorporating how they learn.

That's in contrast to jumping straight to attempting human or cat equivalence, when their method would be obviously inadequate if tested on a simple scale. It'll also take a lot more than just a few researchers to manage the greatest neurological, computational feat in history.

[Simon_Jester]

Is it not unethical to simulate a cat brain to perform research ? Now I know this is an early breakthrough on what remains a long uncharted road. But the argument that brain simulation will allow medical research to be performed that can not be done on live subjects seems pretty dodgy to me. If you are simulating a realistic cat that cat is no different than a biological cat. That makes me a bit upset knowing a virtual kitty is going to die someday.

At a minimum, it is no more unethical than performing equivalent experiments on actual cats would be. Since our choices are "real cat, simulated cat, or don't run the experiment at all..."