Artificial Intelligence
The American Intelligence Advanced Research Projects Activity (IARPA) has recently set up a multi-million dollar initiative aimed at developing brain-inspired computing base principles so it can better understand the challenges and potential opportunities for developing next-generation computer systems.
Harvard University is primed to develop new artificial intelligence systems that work faster, smarter and perhaps better than the human brain. The Intelligence Advanced Research Projects Activity (IARPA) has awarded $28 million to fund this project. The work will also further the overall goals of President Obama's BRAIN Initiative, which aims to improve the understanding of the human mind and uncover new ways to treat neuropathological disorders like Alzheimer's disease, schizophrenia, autism and epilepsy.
IARPA is tasked with figuring out why our brains are so good at learning, and then translate their findings into the design of machine learning systems that can interpret, analyze, and learn information as successfully as humans. The researchers will record activity in the brain’s visual cortex in unprecedented detail, mapping the connectome at a scale never before attempted. They will then reverse-engineer the neural map data in silico and with algorithms inspired by their findings.
"As we figure out the fundamental principles governing how the brain learns, it’s not hard to imagine that we’ll eventually be able to design computer systems that can match, or even outperform, humans."
Researchers will then record brain activity, particularly activity in the visual cortex, in a fashion never done before. They will map "connections at a scale never before attempted" and reverse-engineer the data to create better computer algorithms.“This is a moonshot challenge, akin to the Human Genome Project in scope,” said project leader David Cox, assistant professor of molecular and cellular biology and computer science. “The scientific value of recording the activity of so many neurons and mapping their connections alone is enormous, but that is only the first half of the project. As we figure out the fundamental principles governing how the brain learns, it’s not hard to imagine that we’ll eventually be able to design computer systems that can match, or even outperform, humans.”
This ambitious project will be initiated in Cox’s laboratory, where they will train rats to visually recognize different items on a computer and then record activity inside the visual cortex. A portion of the rat’s brain will then be studied at the lab of project member Jeff Lichtman, where it will be sliced into ultra-thin pieces and imaged.
Related articles
“This is an amazing opportunity to see all the intricate details of a full piece of cerebral cortex,” says Lichtman. “We are very excited to get started but have no illusions that this will be easy.”It is expected that the rat brains alone will generate over a petabyte of data, which is equal to around 1.6 million CDs of information. The data will also be reconstructed with algorithms recognizing and reconstructing the synapses and connections in a three dimensional interactive environment.
Afterwards, it is expected that the biologically-inspired computer algorithms realized from the project will outperform current computer systems in their ability to recognize patterns and make inferences from limited data inputs. Among other things, this research could improve the performance of computer vision systems that can help robots see and navigate through new environments, read MRI images, driving cars and ultimately, just about any other cognitive task we human do.
“We have a huge task ahead of us in this project, but at the end of the day, this research will help us understand what is special about our brains,” Cox said. “One of the most exciting things about this project is that we are working on one of the great remaining achievements for human knowledge — understanding how the brain works at a fundamental level.”
0 comments:
Post a Comment