Harvard University given $28m for AI research
Scientists will try to discover why human brains are better at processing information
Harvard University has been awarded $28m (19m) to help it discover why human brains are better at processing information than artificial intelligence.
The money was contributed by the Intelligence Advanced Research Projects Activity (IARPA), with the end result of hopefully making AI systems more advanced, operating like human brains rather than machines.
The research will look in detail at the storage capacity of human brains, which is assumed to be between 10 and 100 terabytes, although initial studies have suggested it could be a lot more. Additionally, Harvard University will study the functions of the human brain including digging deeper into data analysis, pattern recognition and an ability to learn and retain information.
The research into the brain's visual cortex will be run by Harvard's John A. Paulson School of Engineering and Applied Sciences (SEAS), Centre for Brain Studies (CBS) and Department of Molecular and Cellular Biologies, exposing how neurons in that particular area of the brain can recognise objects, people and more on first sight, rather than taking multiple goes to be able to recognise something, as is the case for AI.
This is thought to be related to how neurons are connected to each other and the researchers will be investigating into how this could potentially be applied to computers, helping them to interpret, analyse and learn information as quickly as the human brain.
"The pattern-recognition and learning abilities of machines still pale in comparison to even the simplest mammalian brains," said Hanspeter Pfister, professor of computer science at Harvard.
"The project is not only pushing the boundaries of brain science, it is also pushing the boundaries of what is possible in computer science. We will reconstruct neural circuits at an unprecedented level from petabytes of structural and functional data. It requires us to make new advances in data management, high-performance computing, computer vision and network analysis."
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