Seed: Out of the Blue
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Saved by 12 people (-3 private), first by anonymouse user on 2008-03-04
- Taryn930 on 2008-04-13 - Tags blue_brain , brain , computer , artificial_intelligence , model , neuro
- Chepedaja on 2008-03-21 - Tags no_tag
- Diigomg on 2008-03-12 - Tags no_tag
- Furlius on 2008-03-12 - Tags science , article , ai
- Rlpowell on 2008-03-07 - Tags Singularity , Psychology
Public Sticky notes
"...Markram speculates that precisely simulating a human brain would require an astronomical volume of processing capacity that would consume a vast quantity of power, but he is confident that a single machine will be able to model a complete human brain in 10 years or less if computing speeds and energy efficiency continue to improve at their current rate."
Highlighted by furlius
Can a thinking, remembering, decision-making, biologically accurate brain be built from a supercomputer?
Highlighted by diigomg
Neuroscience is a reductionist science. It describes the brain in terms of its physical details, dissecting the mind into the smallest possible parts. This process has been phenomenally successful. Over the last 50 years, scientists have managed to uncover a seemingly endless list of molecules, enzymes, pathways, and genes. The mind has been revealed as a Byzantine machine. According to Markram, however, this scientific approach has exhausted itself. "I think that reductionism peaked five years ago," he says. "This doesn't mean we've completed the reductionist project, far from it. There is still so much that we don't know about the brain. But now we have a different, and perhaps even harder, problem. We're literally drowning in data. We have lots of scientists who spend their life working out important details, but we have virtually no idea how all these details connect together. Blue Brain is about showing people the whole."
Highlighted by taryn930
good reason to cite physics—neuroscience has almost no history of modeling. It's a thoroughly empirical discipline, rooted in the manual labor of molecular biology.
Highlighted by taryn930
computational neuroscience. "It's not interested enough in the biology," he says. "What they typically do is begin with a brain function they want to model"—like object detection or sentence recognition—"and then try to see if they can get a computer to replicate that function. The problem is that if you ask a hundred computational neuroscientists to build a functional model, you'll get a hundred different answers. These models might help us think about the brain, but they don't really help us understand it. If you want your model to represent reality, then you've got to model it on reality."
Highlighted by taryn930
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