There's more information about the project here: http://www.humanbrainproject.eu/ http://www.humanbrainproject.eu/files/HBP_flagship.pdf

The project is not actually as absurd as it sounds -- the funding is over 10 years, and it's funding a large number of different research programs in molecular neuroscience (8%), cognitive neuroscience (12%), theoretical neuroscience (6%), neuroinformatics (7%), medical informatics (6%), brain simulation (10%), HPC (18%), neuromorphic computing (14%), robotics (11%), and society/ethics (2%). About half of the budget is going to personnel / students, and the research is being done by a large consortium of established PIs.

Basically, they're creating a "European Institute of Neuroscience". IMHO, the way that it's been branded as as a giant "brain simulation" makes it look a little silly to other scientists -- but on the other hand it seems to have worked pretty well with the politicians.

It's beyond exciting that over a whole percent of the money is going to an ethics line.

Well EU needs to keep humanities grads employed somehow.

But seriously, this project has all the hallmarks of becoming the next Nanotech. As in overly broad, loosely defined, overfunded and with little practical output for the money.

This is such a weird comment I wonder if you were being serious or even read the article.

Are you seriously responding to an article about a research consortium (using a Nobel Prize-winning neuroscientist as an outreach person) by suggesting that they haven't read a book by a tech magnate and a science writer)? I mean, nobody would suggest that Jeff Hawkins is a slouch, but get real. These people are not bumpkins tilting at research money windmills because they haven't seen the light in the best-seller aisle.

You're sure that every member of a worldwide collection of top neuroscientists has no idea about where we're at nowadays regarding AI? Really?

Of course he's sure. He's a hacker. A maker, man. If we were that close to simulating a human brain there would be implementations up on github already, waiting for a $1.6B supercomputer to become available to run it.

> If we were that close to simulating a human brain there would be implementations up on github already

IIRC, the Blue Brain Project uses NEURON.

    hg clone http://www.neuron.yale.edu/hg/neuron/nrn

Indeed it does. If you want to see open source models of the brain check out: http://senselab.med.yale.edu/modeldb/ListByModelName.asp?c=1...

Being outside of academia, I am not privy to the historical reasons that modeldb is the way it is. Something about it has always bothered me.. why on earth are all of these models in different languages? I mean, these aren't exactly CPAN modules or metasploit modules. How are these supposed to be combined reliably? And what about unit tests? what is going on here?

Edit: oh, man :( http://rudylab.wustl.edu/research/cell/methodology/cellmodel...

http://senselab.med.yale.edu/modeldb/ShowModel.asp?model=642...

https://github.com/OpenSourceBrain/Thalamocortical/blob/mast...

last two lines are "sleep(5)" and "exit()" ... that's not how you do python modules :(

Expanding on neuroguy's comment, there's many different people working on making models and pretty much (<simplification>) the only things that matter here are the collections of transfer functions; given inputs, how do outputs propagate. You can see that in the C++ (well, C from the looks of it) example you gave, there's a time value, a timestep, a bunch of physical attributes, and a series of functions - no matter what the language or system used all the other models there have similar features.

When people look at the work of others they are less interested in the modelling system used and more interested in the model, which most are happy to translate to whatever system they are using as the very act of crawling through and translating from one form to another forces a certain kind of deeper look at the details.

It's on par with Watson & Crick using plasticine and paddlepop sticks for their model while others use ping pong balls and wire coat hangers ... further down the track everything gets unified but at the early stages one form of modelling is more or less as good as another.

It is for exactly this reason that the people of http://www.neuroml.org/ are doing their work. Good catch! To combine and place everything in one overarching language that can be used in any of the many Brain Simulators. There are many each with their own advantages, which is why there are so many different languages.

It would be worthwhile to get some more CS guys in the field. Agreed. Please join us :)

While I share some of your misgivings about simulating brains, you do have to remember that giving lots of money to scientists for basic research is bound to come up with something useful and might as well lead to serendipitous results, regardless of hubris or wild ambitions. If only grant proposals that would very likely lead to something would be accepted, then there would be no basic research. The value of basic research is only cashed out much later, if at all.

Their goal is not to create an AI, it is to create a model of the human brain. If you look at their website, you will notice the project is very much a neuroscience research project, not a computer science, AI, research project. The fact that the technical implantation of this project requires specially designed computers and highly algorithms (which will likely merit their own computer science papers), and the fact that this project might produce benefits for computing, does not change the fact that the goal is to understand the human brain through computer modelling, not to create a strong AI.

It seems to me that building a complete model of the human brain would necessarily be identical to creating a strong AI. If they build an incomplete model of a human brain then they have nonetheless created an (incomplete) strong AI.

If they manage to construct a complete model, they would have a strong AI. However, what they are trying to do is construct a model that incorporates everything we know about the human brain. From their, they can better observe how our model compairs to observed reality, and revise it accordingly. They can also test modifications to the model much easier. If they get to the point where their model is also a strong AI it would suggest that they have made great progress in understanding the human brain.

> identical to creating Strong AI

One of the wonderful joys of brain emulation is that you don't have to worry about "designing intelligence into it". Your goal is different; your goal is the human brain itself, without our historical baggage of abstractions like souls, minds, consciousness or intelligence. What if all of those ideas are wrong?

The Human Brain Project's aim is not to create AI - its primary aim is to create a detailed simulation of the Human Brain through big-data integration - in other words through extensive integration of already published data and through integration of strategically selected new-experiments. It is trying to tease out the 'rules' upon which the human brain is built. It has been shown by Henry Markram and his crew that there are in fact rules, which can be simulation, and can explain a great deal of things that would take literally thousands and thousands of experiments - see his connectome paper for an example of how they can predict the connectivity between neurons with a high accuracy - http://www.frontiersin.org/blog/The_Emergent_Connectome/66. The Human Brain Project is composed of a great deal of leading scientists from around the world and their institutions. Do you really think these people (some of which are nobel laureates) are less clued up than the author of "on intelligence". The most pertinent thing to get across here is that the HBP is not an AI project. It is a recreation of the human brain through biophysically accurate models.

"On a positive sidenote $1.6 bn for the duration of this project is peanuts compared to the yearly $140 bn the UE is spending ; )"

On another positive sidenote, the $140B the EU is spending is peanuts compared to the ~$3-4T the US Govt. is spending.