This passage really distills it down to the essence of what happened:
"Despite skepticism in the neuroscience community, Markram won over the people who really mattered: funders at the European Commission, who seem to have looked less closely at the proposal's scientific feasibility than at its potential economic and political payoff."
Given the limited understanding of neuroscience and the problems of Markram's vision, the whole affair had the earmarks of a doomed project.
One can see similar problems in smaller effort by Palm Founder Jeff Hawkin's efforts to jump-start algorithmically oriented neuroscience research with his book On Intelligence and his company Numenta.
With all the failures pretty visible now, I'd like to say I think there's some validity in seeing if one can extract a broad vision out of all the disparate threads of neuroscience research.
There have been events in the history of science when outsiders walked in and saw a forest instead of a lot of trees - see Craig Venter, Alfred Wegener and others (and there have been many more cranks who claimed to the same of course). Making some effort to see if that kind of approach can gel is worth some effort in the study of the brain, a field whose complexity is so huge that gradual, iterative research could continue in places for a thousand years and not answer basic questions.
I was never satisfied with their explanation for why they had to start with the human brain rather than the brain of a MUCH simpler organism like C. elegans.
Exactly. OpenWorm [1] is trying to do exactly that, emulate C. elegans, with all of 302 neurons. It doesn't work yet, but they;'re plugging along. When that problem is totally solved, and the neural model is working right, it's time to move up in complexity. Probably to lizards or birds.
About two decades ago, I heard Rod Brooks talking about building a human brain. He'd done some good artificial insects and was big on purely reactive AI. At the time, he was promoting Cog [2], as a way to get to human-level AI in one big jump. I asked "You've done an insect brain. Why not try to get to a mouse brain next?". He replied "I don't want to go down in history as the man who created the world's greatest robot mouse." 20 years later, Brooks doesn't even have mouse-level AI, although he does have a robotic vacuum cleaner company.
A mouse has about 1g of brain mass; a human has about 1000g. But they're both mammals, with about 90% similar DNA. If someone could simulate a mouse at the neural simulation level, that would be real progress. Once you have a mouse simulation, human level is a scaling problem.
The Human Brain Project blew through a billion dollars in funding while OpenWorm is a volunteer effort. That's the real problem.
Exactly. So much of neuroscience is still in "unknown unknown" phase, and the idea of just doing this massive interdisciplinary project to simulate a full human brain, built on the pile of sand that is any sort of "theory" of full-brain simulation ... it's like dedicating $1 billion to some dude's unpublished idea of proving P = NP. Bullshit should have been called before this ever got off the drawing board.
Sure seems like the EU has it's fair share of incompetent technocrats if you can throw $1 billion at some nonsense any handful of PhDs in the field could have told you was nonsense if you'd just picked up a phone.
Because it's unlikely that C. elegans can't even learn. It doesn't have any brain structures equivalent to ones in humans. It's neurons work totally differently. They are so different from us that anything we learn probably wouldn't apply to human brains. A more intelligent animal, ideally a mammal, would be a much better choice.
John Cleese, of all people, summarized our current knowledge of the nervous system best in this video: https://youtu.be/FQjgsQ5G8ug?t=20
We are clueless. A lot of what is published is just neurobabble, even in 'serious' journals. As others have pointed out, we still don't even know how to simulate a brain of a tiny worm with 302 neurons. Talking about simulating billions of neurons is beyond fantasy, and funding such a projects is.. well.. not surprising from politicians, but that is another matter.
Similarly, a lot of scientists are researching themes like 'consciousness' and 'executive functions' and still don't know how to make a robot walk like a normal person on two feet. We should be concentrating on trying to understand the simple stuff - the reflex arc, muscle control, grasping, and pointing a finger toward something.
[Ok, I just saw in another one of you're posts your MA involved perceptual control theory, so yah, right on. I have this written already and feel a little silly now, but I figure the links are good and worth posting.]
I am finishing up my undergraduate right now in psychology, and while I want to defend the work that is being done by cognitive psychologists on concepts at higher levels of abstraction (Many researchers working in more mathematical areas of psychology tend towards working on things like consciousness, perception, concepts and categorization. There are cool advances in it, but I won't go too much into it in this post. I guess I'm just trying to say that you end up working with constructs that have higher barriers of entry to communicating outside of groups of researchers who get excited about modeling and the perceptual measurement theory.) I digress with that though. The main reason I wanted to comment is that your comment on understanding things like pointing hit on one of my favorite areas of psychology that has tragically always been somewhat nitch, but provides a lot of interesting connections between different areas if you take the time to get into it. There is a thread in the field of psychology that does just this kind of research, termed sometimes ecological psychology. It is often referred to colloquially as Gibsonian psychology, termed after [JJ Gibson](https://en.wikipedia.org/wiki/James_J._Gibson) who is seen as the father of the field(its practitioner's are known colloquially as Gibsonians).
I was lucky enough to take the Geoffrey Bingham's (who specializes reach to grasp behavior iirc) Perception/Action course a few years back, and found it immensely rewarding.* The primary text for the course was JJ Gibson's classic book "The Ecological Approach to Visual Perception". The philosophical foundations of gibsons theory of affordances is to take a realist approach to perception. (Avoiding the troubles that mind-body dualism imposes; taking a more Heidegerrian approach). The classic mantra of the field is ask not what is in you're mind, but what you're mind is in.
I wish I had time to say more now, but I need to run here.
But I'll leave you with a few snippets of what I took away from the course, and some links I think you'll enjoy, and can furnish more if you would be interested.
The Archival Gibson Video Series (Whoever assembled these had perfect choice in music)
Like any project, I'm sure there are many ways it can be improved.
Still, I'd much rather see $1B spent imperfectly on something important - a thousand times over - rather than a trillion plus on the F-35, or so many of the ways governments spend money.
No results from a wahatever effort is still axwaste no matter how wonderful the payoff might have been. This goes to the heart of why efforts like this get funding in the first place. The funding committees get blinded by the bright light of the potential payoff, and the money gets wasted instead of going to fund and actualy deliver valuable projects that aren't as glitzy. But at least you would have ended up with a real actual benefit.
IBM started questioning their funding of the project because of the lack of a success criteria.
It's cool that you have many calculations running in parallel on a super computer, and each calculation is a simplified model of a neuron, but how do you know when you've actually replicated a brain? A brain is more than a collection of neurons, they need to be connected and do something.
In the current era, technological advances are far more important to progress in the life sciences than ideas or analytical/computational methods. The cycle of innovation is quite fast. The human genome project is a classic example. Celera genomics came out with a a totally new DNA sequencing technology towards the end of the HGP, and managed to sequence the human genome in a fraction of the time. It so happens that the HGP had enough of a head start to release their data at the same time, and that their data and Celera's data were complementary in many ways. But imagine if the HGP started 5 years later, and Celera released their complete genome when HGP had only done 50%? It too would be considered a grand failure.
A grand project needs to be timed very carefully. Even the ones that actually work well will be obsolete by their completion unless they happen to occur in the right part of the technology cycle.
A 10 part documentary is being made by film director Noah Hutton, with each installment detailing the year-long workings of the project at the EPFL. Having started filming in 2009, the documentary is planned to be released in 2020, after the years of filming and editiang have finished. Regular contributions from Henry Markram and the rest of the team provide an insight into the Blue Brain Project, while similar research tasks across the world are touched on.
>While he was still in Germany, his son Kai had been diagnosed with autism. As he told The Guardian in 2013, he wanted “to be able to step inside a simulation of my son's brain and see the world as he sees it.”
Or terrifying, if you consider that a simulation of his son's brain is, in a very real sense, his son. And that when he shuts that simulation down he's killing it.
I might go so far as to say that the issue isn't with the management structure so much as the complete lack of a management structure. It takes a well run and managed organization to spend a billion euros effectively.
[+] [-] freshhawk|10 years ago|reply
"Despite skepticism in the neuroscience community, Markram won over the people who really mattered: funders at the European Commission, who seem to have looked less closely at the proposal's scientific feasibility than at its potential economic and political payoff."
[+] [-] joe_the_user|10 years ago|reply
One can see similar problems in smaller effort by Palm Founder Jeff Hawkin's efforts to jump-start algorithmically oriented neuroscience research with his book On Intelligence and his company Numenta.
With all the failures pretty visible now, I'd like to say I think there's some validity in seeing if one can extract a broad vision out of all the disparate threads of neuroscience research.
There have been events in the history of science when outsiders walked in and saw a forest instead of a lot of trees - see Craig Venter, Alfred Wegener and others (and there have been many more cranks who claimed to the same of course). Making some effort to see if that kind of approach can gel is worth some effort in the study of the brain, a field whose complexity is so huge that gradual, iterative research could continue in places for a thousand years and not answer basic questions.
[+] [-] rndn|10 years ago|reply
[+] [-] streptomycin|10 years ago|reply
[+] [-] Animats|10 years ago|reply
About two decades ago, I heard Rod Brooks talking about building a human brain. He'd done some good artificial insects and was big on purely reactive AI. At the time, he was promoting Cog [2], as a way to get to human-level AI in one big jump. I asked "You've done an insect brain. Why not try to get to a mouse brain next?". He replied "I don't want to go down in history as the man who created the world's greatest robot mouse." 20 years later, Brooks doesn't even have mouse-level AI, although he does have a robotic vacuum cleaner company.
A mouse has about 1g of brain mass; a human has about 1000g. But they're both mammals, with about 90% similar DNA. If someone could simulate a mouse at the neural simulation level, that would be real progress. Once you have a mouse simulation, human level is a scaling problem.
The Human Brain Project blew through a billion dollars in funding while OpenWorm is a volunteer effort. That's the real problem.
[1] http://www.openworm.org/ [2] http://www.ai.mit.edu/projects/humanoid-robotics-group/cog/c...
[+] [-] themgt|10 years ago|reply
Sure seems like the EU has it's fair share of incompetent technocrats if you can throw $1 billion at some nonsense any handful of PhDs in the field could have told you was nonsense if you'd just picked up a phone.
[+] [-] Houshalter|10 years ago|reply
[+] [-] gohrt|10 years ago|reply
http://nemaload.davidad.org/
[+] [-] amatic|10 years ago|reply
We are clueless. A lot of what is published is just neurobabble, even in 'serious' journals. As others have pointed out, we still don't even know how to simulate a brain of a tiny worm with 302 neurons. Talking about simulating billions of neurons is beyond fantasy, and funding such a projects is.. well.. not surprising from politicians, but that is another matter.
Similarly, a lot of scientists are researching themes like 'consciousness' and 'executive functions' and still don't know how to make a robot walk like a normal person on two feet. We should be concentrating on trying to understand the simple stuff - the reflex arc, muscle control, grasping, and pointing a finger toward something.
[+] [-] aggerdmon|10 years ago|reply
I am finishing up my undergraduate right now in psychology, and while I want to defend the work that is being done by cognitive psychologists on concepts at higher levels of abstraction (Many researchers working in more mathematical areas of psychology tend towards working on things like consciousness, perception, concepts and categorization. There are cool advances in it, but I won't go too much into it in this post. I guess I'm just trying to say that you end up working with constructs that have higher barriers of entry to communicating outside of groups of researchers who get excited about modeling and the perceptual measurement theory.) I digress with that though. The main reason I wanted to comment is that your comment on understanding things like pointing hit on one of my favorite areas of psychology that has tragically always been somewhat nitch, but provides a lot of interesting connections between different areas if you take the time to get into it. There is a thread in the field of psychology that does just this kind of research, termed sometimes ecological psychology. It is often referred to colloquially as Gibsonian psychology, termed after [JJ Gibson](https://en.wikipedia.org/wiki/James_J._Gibson) who is seen as the father of the field(its practitioner's are known colloquially as Gibsonians).
I was lucky enough to take the Geoffrey Bingham's (who specializes reach to grasp behavior iirc) Perception/Action course a few years back, and found it immensely rewarding.* The primary text for the course was JJ Gibson's classic book "The Ecological Approach to Visual Perception". The philosophical foundations of gibsons theory of affordances is to take a realist approach to perception. (Avoiding the troubles that mind-body dualism imposes; taking a more Heidegerrian approach). The classic mantra of the field is ask not what is in you're mind, but what you're mind is in. I wish I had time to say more now, but I need to run here. But I'll leave you with a few snippets of what I took away from the course, and some links I think you'll enjoy, and can furnish more if you would be interested.
The Archival Gibson Video Series (Whoever assembled these had perfect choice in music)
[Reversibility and event perception](https://www.youtube.com/watch?v=GwVLny6Ymsk)
[Optical Transitions:Visible To Invisible](https://www.youtube.com/watch?v=1qQLtIICXoE)
[Motion Paralax and Percieved Depth](https://www.youtube.com/watch?v=bVSaWXqQh0w)
Disclaimer I haven't watched this video, but the idea that perception of throw-ability may explain size weight illusions is a surprising one.
[Geoff Bingham - Haptics: throwing and the size-weight illusion](https://www.youtube.com/watch?v=Ud9JB4NYUvA)
* I really need to digitize those notes...
Btw: Awesome Arm.
[+] [-] paulsutter|10 years ago|reply
Still, I'd much rather see $1B spent imperfectly on something important - a thousand times over - rather than a trillion plus on the F-35, or so many of the ways governments spend money.
[+] [-] simonh|10 years ago|reply
[+] [-] ktRolster|10 years ago|reply
It's cool that you have many calculations running in parallel on a super computer, and each calculation is a simplified model of a neuron, but how do you know when you've actually replicated a brain? A brain is more than a collection of neurons, they need to be connected and do something.
[+] [-] Gatsky|10 years ago|reply
A grand project needs to be timed very carefully. Even the ones that actually work well will be obsolete by their completion unless they happen to occur in the right part of the technology cycle.
[+] [-] g7635629|10 years ago|reply
https://www.youtube.com/watch?v=FhsZll_P1iA
[+] [-] skimpycompiler|10 years ago|reply
https://en.wikipedia.org/wiki/Blue_Brain_Project#Documentary
This is going to be very interesting.
[+] [-] Moshe_Silnorin|10 years ago|reply
This is a beautiful sentiment.
[+] [-] taneq|10 years ago|reply
[+] [-] rasz_pl|10 years ago|reply
800 scientists: We Jelly JO! How come one asshole gets 1.3B euro for his project and can decide how to spend it? Lets collectively shit on him.
There is no substantive critique cited in this article, only scientists whining about management structure.
[+] [-] hyperion2010|10 years ago|reply
[+] [-] unknown|10 years ago|reply
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