The Blue Brain Project was able to simulate part of the brain during a thought.
Many of you, like me, are excited about the possibilities of modeling and simulating the human brain. The Blue Brain Project, based in Switzerland, and made possible by IBM, is one of the leading endeavors to understand how the brain functions and how we can build a computer that will simulate those functions for us to explore. If our earlier article on the Blue Brain Project left you eager to learn more, check out the new presentation that Project Director Henry Markram gave as part of Seed Magazine‘s Seed Design Series. The 15 minute video is embedded after the break.
If you want to understand something, it helps to be able to explore it, tinker with it, and watch how it works. Computer simulations allows scientists to do just that. For an instrument as complex and beautiful as the human brain, a simulation would require enormous resources. Markram estimates that it will take computers 20,000 times more powerful than any produced today, and with memory capacity 500 times the current size of the Internet. We’re talking exaflops worth of computing power and peta or exabytes of memory stored. Yet Markram seems confident we can reach these goals in about 10 years.
Markram does a good job of breaking down Blue Brain’s approach, as does our earlier article, so I won’t repeat it all. The focus of the simulation is the neocortex, specifically microprocessors in neocortical columns. So far BBP has been able to make 3D models, examining the over 400 types of neurons, electrical signal profiles, protein profiles, connectivity patterns, and signal languages in the neocortex. The journey through the brain that Markram gives you is really cool, especially when he reveals it’s only at 10% density of the actual brain. Apparently neurons are more densely packed than geeks at a comicon.
BBP is not an effort to create an artificial intelligence, it’s an attempt to model how the brain works. As such, its ability to help us explore and treat brain disease has great potential. Markram touches briefly on medical applications such as researching Autism near 12:02.
The modeling and simulating of the human brain is a herculean feat, and many detractors claim it can never be fully accomplished. Some wonder if a simulation can even discover anything new as it is only based on supplied information not nature itself. While I can’t address the latter, I know that the scope of the project shouldn’t let you scoff at Markram’s 10 year prediction. After all, the Human Genome Project seemed equally daunting, but was achieved with historic results. Whether it takes a decade, or more, I look forward to a time when humans can explore a virtual version of the instrument that allows them to explore the world.
Comments
Wow, amazing work…
After 40 years of studying the human brain, that is its neocortex, I have logically concluded that the neocortex is no more than layers of mutually inhibiting excitatory neurons with layer feedbacks for short term memory. Glial cells control axonal growth which is obeying Pavlov conditioning rules. The mutually inhibiting groups automatically perform normalized cross-correlations between axonal input patterns and axonal connection patterns, where the normalization is due to the fact that inhibitory connections grow proportional to the square root of the sum of the squares of the axonal connection strengths to a neuron.
Dr. Ronald J. Swallow
610 704 0914
[email protected]
After 40 years of studying the human brain, that is its neocortex, I have logically concluded that the neocortex is no more than layers of mutually inhibiting excitatory neurons with layer feedbacks for short term memory. Glial cells control axonal growth which is obeying Pavlov conditioning rules. The mutually inhibiting groups automatically perform normalized cross-correlations between axonal input patterns and axonal connection patterns, where the normalization is due to the fact that inhibitory connections grow proportional to the square root of the sum of the squares of the axonal connection strengths to a neuron.
Dr. Ronald J. Swallow
610 704 0914
[email protected]
Let’s put 2029 in context:
It means that a human born today will be as smart as the best computer when he is 20 years old.
He will be half as smart as the best computer by the age of 23 or 24.
By the time he is 40 years old?
That exponential explosion of machine intelligence is the essence of the concept of the “Singularity”.
However, some years before that, semi-intelligent AI scripts will have long since obsoleted most human labor.
Let’s put 2029 in context:
It means that a human born today will be as smart as the best computer when he is 20 years old.
He will be half as smart as the best computer by the age of 23 or 24.
By the time he is 40 years old?
That exponential explosion of machine intelligence is the essence of the concept of the “Singularity”.
However, some years before that, semi-intelligent AI scripts will have long since obsoleted most human labor.
Although this isn’t an AI project, isn’t it exactly what AI brain simulation projects want to do?
Although this isn’t an AI project, isn’t it exactly what AI brain simulation projects want to do?
A) Kurzweil predicts 2029 I believe for the coming of a brain-capable computer. I think he means the first ever, not one-in-every-home, but if this guy is right, it’ll be about one-in-every-home by 2029. It took roughly 30 years from the dawn of electronic computers to the beginning of home penetration. Right now the computer I have would be classified as a shit-hot supercomputer about 10 years ago (all but the two most powerful from June 1999 are less powerful than my desktop computer http://www.top500.org/lists/1999/06 ). That means that today’s top supercomputers are going to be under our desks by 2019. Holy. Shit.
B) If we can imagine it, we can probably do it. (For instance, if we can figure out a way to precisely split 3 protons out of lead, we would end up with gold. It may not be practical but it does lie within the realm of possibility.)
C) Of course it’s possible to simulate the brain. There is a very definite physical structure to it, it’s only so large, we know fairly precisely what lies in it and are refining that knowledge daily. It is only a matter of time and money.
A) Kurzweil predicts 2029 I believe for the coming of a brain-capable computer. I think he means the first ever, not one-in-every-home, but if this guy is right, it’ll be about one-in-every-home by 2029. It took roughly 30 years from the dawn of electronic computers to the beginning of home penetration. Right now the computer I have would be classified as a shit-hot supercomputer about 10 years ago (all but the two most powerful from June 1999 are less powerful than my desktop computer http://www.top500.org/lists/1999/06 ). That means that today’s top supercomputers are going to be under our desks by 2019. Holy. Shit.
B) If we can imagine it, we can probably do it. (For instance, if we can figure out a way to precisely split 3 protons out of lead, we would end up with gold. It may not be practical but it does lie within the realm of possibility.)
C) Of course it’s possible to simulate the brain. There is a very definite physical structure to it, it’s only so large, we know fairly precisely what lies in it and are refining that knowledge daily. It is only a matter of time and money.
I look forward to the success of the project, to explore what we once consider the impossible. Apart from Autism perhaps Alzheimer.
I look forward to the success of the project, to explore what we once consider the impossible. Apart from Autism perhaps Alzheimer.