In a recent breakthrough, the Government is now betting $28 million dollars against all of the projects in this field believing that they all go wrong.
The question of making a computer that works like a human is now seeming as if the scientific communtiy is on the wrong tracks.
A series of three grants snagged by Harvard University from the Intelligence Advanced Research Projects Activity (IARPA) last week has funded a “moonshot” project to throw out all previous attempts towards assimilating the human brain and begin with a fresh start.
(IARPA is the sibling organization to the better-known Defense Advanced Research Projects Agency, or DARPA. But while DARPA focuses on military projects, IARPA focuses on intelligence agency research.)
This 5-year project will try to build a virtual model of a rat brain while the rat is learning. From this, the lab hopes to be able to identify the way organic neurons work together to learn, so they can replicate it artificially. Ultimately, the desired result is to replicate the human brain itself.
“It’s a reverse engineering expedition,” said David Cox, Professor at Harvard and leader of the project. “If your competitor released a product and it was way better than your product, you might buy the product, open it up, and try to figure out how it works. Nature is the competing company in this scenario.”
The basic methodology of the project is to show live rats a series of images while examining their brains under a microscope. This information is later correlated to a virtual representation of the brain, made when the rats’ brains are cut into small sections and imaged under an electron microscope.
Harvard University says that the whole project will produce more than a petabyte of information, which will be made publicly available. (A petabyte is equivalent to an mp3 audio track 2000 years long.)
Having all of this data will be great, but one thing that we already know is that the rodent brain works differently than the human brain does.
Once acknowledging that, Cox believes that the methods used to virtually replicate the brain in this project could be valuable in their later application to humans. Replicating rat brains can be compared to children using training wheels, except that replicating the human brain is the desired end goal one day. So in a sense, this project might be a first step to neural maps being employed in regular human treatment, albeit far into the future.
With electron microscopy, the Harvard teams will be able to reconstruct the “wiring diagrams” of the brain, Cox says. They’ll be able to see in real-time which neurons are collaborating with one another, and how the connections are shaped.
"Nature is the competing company in this scenario."
Understanding the brain is a huge step in neuroscience, but this project’s main thrust is actually aimed at computer science. Modeling the brain is only the first step. After (and potentially during) the creation of the model, researchers are tasked with creating algorithms that replicate the way that the brain processes information. That is the task that artificial intelligence researchers have been grappling with for more than 50 years in the making. Currently, most A.I. research heavily relies on statistics rather than biology.
“We know that brains are really good at things like learning and inference, but we don’t yet have algorithms that can match those abilities,” Cox said. “But we’re not completely on a limb without an idea. We know the shape of the book, but we need to know the words inside.”
However, Cox says that most researchers, like those working with DARPA’s Synapseproject and Europe’s Human Brain Project are jumping head first into creating models of the brain without first fully comprehending how the brain works. The Synapse Project, which is largely pioneered by IBM, has already created chips based on previous knowledge of the brain. The Human Brain Project is also building models on “existing data,” according to their research goals.
Meanwhile, the IARPA project will span five years, and will be allocated over three stages. Each stage will study a larger portion of the brain, with the largest being just a one millimeter cube.
Source:
Dave Gershgorn
Popular Mechanic
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