Strong AI is, for many, the “holy grail” of computing and in general terms means the development of a machine that thinks as well or better than a human.    Computers already have surpassed humans in most very focused intelligence tasks such as mathematical calculations, game playing, most forms of data analysis, and many more of the tasks we often use to define  ”intelligence”.     However no machine comes close to the capabilities of a full human brain at this time, our remarkable three pound package that includes a high level of consciousness and self-awareness, adaptive mechanisms, deep creativity, and more.

With a fairly modest budget compared to the DARPA SyNAPSE,  Brain-i-nets goals appear more modest.   Science Daily suggests the goal as:

The scientists want to design a new generation of neuro-computers based on the principles of calculation and learning mechanisms found in the brain, and at the same time gain new knowledge about the brain’s learning mechanisms.

The Brain-i-nets website puts this …. somewhat differently, leading one to wonder if they were writing for public understanding or a science fiction movie script:

The goal of this project is to produce a set of rules for synaptic plasticity and network reorganisation that describe the actual adaptive processes that take place in the living brain during learning and to port these rules into current and next-generation neuromorphic hardware.

“Future Emerging Technologies” (FET) is the key agency behind   “Brain-i-Nets” which appears to have a budget of about 2.6 million Euros (though I’m not clear if this is just the matching partner funding or the entire budget).

The research partnership includes the University College London, the Ecole Polytechnique Federale de Lausanne, the French Centre National de la Recherche Scientifique, Ruprecht-Karls-Universität Heidelberg und the University of Zurich.

——   Guest Post by Dr. Henry Markram of the Blue Brain Project —-

IBM’s claim is a HOAX.

This is a mega public relations stunt – a clear case of scientific deception of the public. These simulations do not even come close to the complexity of an ant, let alone that of a cat. IBM allows Mohda to mislead the public into believing that they have simulated a brain with the complexity of a cat – sheer nonsense.

Here are the scientific reasons why this is a hoax and misleading PR stunt:

How complex is their model?
They claim to have simulated over a billion neurons interacting. Their so called “neurons” are the tiniest of points you can imagine, a microscopic dot. Over 98% of the volume of a neuron is branches (like a tree). They just cut off all the branches and roots and took a point in the middle of the trunk to represent a entire neuron. In real life, each segment of the branches of a neuron contains dozens of ion channels that powerfully controls the information processing in a neuron. They have none of that. Neurons contain 10′s of thousands of proteins that form a network with 10′s of millions of interactions. These interactions are incredibly complex and will require solving millions of differential equations. They have none of that. Neurons contain around 20’000 genes that produce products called mRNA, which builds the proteins. The way neurons build proteins and transport them to all the corners of the neuron where they are needed is an even more complex process which also controls what a neuron is, its memories and how it will process information. They have none of that. 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. Synapses are also extremely complex molecular machines that would themselves require thousands of differential equations to simulate just one. They simulated none of this. There are complex differential equations that must be solved to simulate the ionic flow in the branches, to simulate the ion channels biophysics, the protein-protein interactions, as well as the complete biochemical and genetic machinery as well as the synaptic transmission between neurons. 100′s of thousands of more differential equations. They have none of this. Then there are glia – 10 times more than neurons..And the blood supply…and more and more. These “points” they simulated and the synapses that they use for communication are literally millions of times simpler than a real cat brain. So they have not even simulated a cat’s brain at more than one millionth of it’s complexity.

Is it nonetheless the biggest point neuron simulation ever run?
No. These people simulated 1 billion points interacting. They used a formulation to model the summing up and threshold spiking of the “points” called the Izhikevik Formulation (an extremely simple equation). Eugene Izhikevik himself already in 2005 ran a simulation with 100 billion such points interacting just for the fun of it: (over 60 times larger than Modha’s simulation). This simulation ran on a cluster of desktop PCs and which every graduate student can run This is no technical achievement and certainly not even a record number of point neurons. That model exhibited oscillations, but that always happens so even simulating 100 Billion such points interacting is light years away from a brain.
see: http://www.izhikevich.org/human_brain_simulation/Blue_Brain.htm#Simulation%20of%20Large-Scale%20Brain%20Models

Is the simulator they built a big step?
Not even close. There are numerous proprietary and peer-reviewed neurosimulators (e.g., NCS, pNEURON, SPLIT, NEST) out there that can handle very large parallel models that are essentially only bound by the available memory. The bigger the machine you have available, the more neurons you can simulate. All these simulators apply optimizations for the particular platform in order to make optimal use of the available hardware. Without any comparison to existing simulators, their publication is a non-peer reviewed claim.

Did they learn anything about the brain?
They got very excited because they saw oscillations. Oscillations are an obligatory artifact that one always gets when many points interact. These findings that they claim on the neuroscience side may excite engineers, but not neuroscientists.

Why did they get the Gordon Bell Prize?
They submitted a non-peer reviewed paper to the Gordon Bell Committee and were awarded the prize almost instantly after they made their press release. They seem to have been very successful in influencing the committee with their claim, which technically is not peer-reviewed by the respective community and is neuroscientifically outrageous.

But is there any innovation here?
The only innovation here is that IBM has built a large supercomputer – which is irrelevant to the press release.

Why did IBM let Mohda make such a deceptive claim to the public?
I don’t know. Perhaps this is a publicity stunt to promote their supercompter. The supercomputer industry is suffering from the financial crisis and they probably are desperate to boost their sales. It is so disappointing to see this truly great company allow the deception of the public on such a grand scale.

But have you not said you can simulate the Human brain in 10 years?
I am a biologist and neuroscientist that has studied the brain for 30 years.  I know how complex it is. I believe that with the right resources and the right strategy it is possible. We have so far only simulated a small part of the brain at the cellular level of a rodent and I have always been clear about that.

Would other neuroscientists agree with you?
There is no neuroscientist on earth that would agree that they came even close to simulating the cat’s brain – or any brain.

But did Mohda not collaborate with neuroscientists?
I would be very surprised if any neuroscientists that he may have had in his DARPA consortium realized he was going to make such an outrages claim. I can’t imagine that that the San Fransisco neuroscientists knew he was going to make such a stupid claim. Modha himself is a software engineer with no knowledge of the brain.

But did you not collaborate with IBM?
I was collaborating with IBM on the Blue Brain Project at the very beginning because they had the best available technology to faithfully allow us to integrate the diversity and complexity found in brain tissue into a model. This for me is a major endeavor to advance our insights into the brain and drug development. Two years ago, when the same Dharmendra Mhoda claimed the “mouse-scale simulations”, I cut all neuroscience collaboration with IBM because this is an unethical claim and it deceives the public.

What IBM allowed Modha to do here is not only wrong, but outrageous. They deceived millions of people.

Henry Markram
Blue Brain Project

SyNAPSE seeks not just to build brain-like chips, but to define a fundamentally distinct form of computational device. These new devices will excel at the kinds of distributed, data-intensive algorithms that complex, real-world environment require…

It’s very exciting stuff this “build a brain” competition.  Although I think the theoretical approach taken by Blue Brain is more consistent with what little we know about how brains work, I’d guess SyNAPSE’s access to DARPA funding will give it the long term edge in terms of delivering a functional thinking machine in the 15-20 year time frame most artificial intelligence researches believe we’ll need for that ambitious goal.

My optimism is greater than many because I think humans have rather dramatically exaggerated the complexity of their own feeble mental abilities by a quite a … bit, and I’d continue to argue that consciousness is much more a function of quantity than quality.

Another promising development in the artificial brain area is in Spain where  Blue Brain project partner universities are working on the project:  Cajal Blue Brain

Although it is not the stated goal of the project which is designed primarily to help understand the brain and diagnose brain disorders, the Blue Brain project may be the first to deliver a true “Artificial Intelligence” via this process of reverse engineering.

Thankfully the recent rumor reporting a problem between IBM and the Blue Brain project appears to be false. Technology Report has confirmed with IBM Switzerland that the Blue Brain project is waiting for Phase II funding from the Swiss Government. See the statement from Blue Brain project director Henry Markam below.

A recent intriguing development with Gamma oscillations and the Blue Brain AI simulation is reported here at Neuronism.

Henry Markram, Project Director as quoted by IBM Switzerland to Technology Report on January 19, 2009:

The funding:
There is a serious misconception that IBM somehow funded or donated to
support the Blue Brain Project. The BBP project is funded primarily by the
Swiss government and secondarily by grants and some donations from private
individuals. The EPFL bought the BG, it was not donated to the EPFL. It was
at a reduced cost because at that stage it was still a prototype and IBM
was interested in exploring how different applications will perform on the
machine – we were a kind of beta site.

The Collaboration:
The Blue Brain Project is a project that I conceived over the past 15
years. I chose the name because of the Blue Gene series which is a
fantastic architecture for brain simulations. When we bought the BG, we
also had to make sure that we have the computer engineering and computer
science expertise to run the machine and optimize all the programs. So BG
came to us with IBM’s full support as a technology partner. This component
of the collaboration is invaluable to the Project and will continue and
grow as long as we have a Blue Gene or other architectures from IBM. This
is by far the major component of the collaboration.

IBM Research at T.J. Watson, also contributed a postdoc that was sent to
work with us at the EPFL and assigned a researcher at Watson to work on
some computational neuroscience tasks. The research and term assigned to
these postdocs is done, a success and published. Actually, the term expired
almost a year ago, and the IBM postdoc, Sean Hill, actually transfered and
is now an employee of the BBP and not IBM. The researcher at TJ Watson
worked on a specific problem of collision detection between the axons and
dendrites and this is done very well and already published. Although very
important projects and contributions, this is a small part of the BBP which
is carried out at the EPFL and involves, neuroscience, neuroinformatics,
vizualization, and a vast spectrum of computational neuroscience.

Continuation:
BBP needs BG’s to continue the project. The architecture is perfect for
brain simulations. When we manage to get our funding to buy the next BG/P
finalized, we will start Phase 2 and that will of course involve the basic
(and most significant) technology collaboration, and most likely also many
new collaborations on specific research targeted topics where we see that
IBM can, and would like to, contribute. So this is an intermediate phase
while we get ready for phase 2 – molecular level modeling.

BBP sees IBM as a key partner in the BBP and I do think that IBM also sees
the value in the BBP. We are getting ready for Phase 2, but it has not
started until we get the next BG series.

More about Blue Brain is here