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4 months ago
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Australian Researchers Awarded Funding to Merge AI with Human Brain Cells
A team of researchers at Melbourne's Monash University has received over $400,000 in federal funding to merge human brain cells with artificial intelligence. This groundbreaking research aims to grow human brain cells on silicon chips and teach them to perform goal-directed tasks. The funding came from the National Intelligence and Security Discovery Research Grants Program.
Led by Associate Professor Adeel Razi and in collaboration with start-up Cortical Labs, the project involves growing approximately 800,000 brain cells in a laboratory dish. The team has already gained attention for demonstrating the cells' ability to play the game Pong while living in a dish, which was published in the journal 'Neuron'. Razi believes that this technology has the potential to surpass current silicon-based hardware and will have significant implications across various fields.
The project received funding due to the need for a new type of machine intelligence that can learn throughout its lifetime. Artificial intelligence technology struggles to acquire new skills without compromising old ones and suffers from "catastrophic forgetting."In contrast, human brains excel at continual lifelong learning. The researchers aim to develop AI machines that replicate the learning capacity of biological neural networks.
This research aims to scale up the hardware and methods capacity to where biological neural networks become a viable replacement for in silico computing. By understanding the biological mechanisms of lifelong continual learning, the team hopes to develop better AI machines. This advancement could revolutionize planning, robotics, advanced automation, brain-machine interfaces, and drug discovery.
Key Points:
- Melbourne's Monash University has received $403,000 in federal funding for merging human brain cells with AI.
- The project involves growing 800,000 brain cells on silicon chips and teaching them goal-directed tasks.
- Current AI technology struggles with acquiring new skills and suffers from "catastrophic forgetting."
- The researchers aim to develop AI machines that replicate the lifelong learning capacity of human brains.
- The ultimate goal is to replace traditional in silico computing with biological neural networks.
Reference: [1].
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