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Mapping the Brain to Build Better Machines Quanta Magazine

#artificialintelligence

Take a three year-old to the zoo, and she intuitively knows that the long-necked creature nibbling leaves is the same thing as the giraffe in her picture book. That superficially easy feat is in reality quite sophisticated. The cartoon drawing is a frozen silhouette of simple lines, while the living animal is awash in color, texture, movement and light. It can contort into different shapes and looks different from every angle. Humans excel at this kind of task.


A Map of the Brain Could Teach Machines to See Like You

AITopics Original Links

Take a three-year-old to the zoo, and she intuitively knows that the long-necked creature nibbling leaves is the same thing as the giraffe in her picture book. That superficially easy feat is in reality quite sophisticated. The cartoon drawing is a frozen silhouette of simple lines, while the living animal is awash in color, texture, movement and light. It can contort into different shapes and looks different from every angle. Humans excel at this kind of task.


A Map of the Brain Could Teach Machines to See Like You

#artificialintelligence

Take a three-year-old to the zoo, and she intuitively knows that the long-necked creature nibbling leaves is the same thing as the giraffe in her picture book. That superficially easy feat is in reality quite sophisticated. The cartoon drawing is a frozen silhouette of simple lines, while the living animal is awash in color, texture, movement and light. It can contort into different shapes and looks different from every angle. Humans excel at this kind of task.


The U.S. Government Launches a $100-Million "Apollo Project of the Brain"

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Three decades ago, the U.S. government launched the Human Genome Project, a 13-year endeavor to sequence and map all the genes of the human species. Although initially met with skepticism and even opposition, the project has since transformed the field of genetics and is today considered one of the most successful scientific enterprises in history. Now the Intelligence Advanced Research Projects Activity (IARPA), a research organization for the intelligence community modeled after the defense department's famed DARPA, has dedicated $100 million to a similarly ambitious project. The Machine Intelligence from Cortical Networks program, or MICrONS, aims to reverse-engineer one cubic millimeter of the brain, study the way it makes computations, and use those findings to better inform algorithms in machine learning and artificial intelligence. IARPA has recruited three teams, led by David Cox, a biologist and computer scientist at Harvard University, Tai Sing Lee, a computer scientist at Carnegie Mellon University, and Andreas Tolias, a neuroscientist at the Baylor College of Medicine.


Largest network of cortical neurons mapped from 100 terabytes data set

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Neuroscientists have constructed a network map of connections between cortical neurons, traced from a 100 terabytes 3D data set. The data were created by an electron microscope in nanoscopic detail, allowing every one of the "wires" to be seen, along with their connections. Some of the neurons are color-coded according to their activity patterns in the living brain. The largest network of the connections between neurons in the cortex to date has been published by an international team of researchers from the Allen Institute for Brain Science, Harvard Medical School, and Neuro-Electronics Research Flanders (NERF). In the process of their study*, the researchers developed new tools that will be useful for "reverse engineering the brain by discovering relationships between circuit wiring and neuronal and network computations," says Wei-Chung Lee, Ph.D., Instructor in Neurobiology at Harvard Medicine School and lead author of a paper published this week in the journal Nature.