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Research merging human brain cells with silicon chips receives national security grant

The Monash University-led research received nearly $600,000 in funding from the National Intelligence and Security Discovery Research Grants Program, where researchers hope to teach the lab-grown brain cells tasks.

The Monash University-led research received nearly $600,000 in funding from the National Intelligence and Security Discovery Research Grants Program, where researchers hope to teach the lab-grown brain cells tasks.

The program will be headed by Associate Professor Adeel Razi from the Turner Institute for Brain and Mental Health, in collaboration with the Melbourne-based start-up Cortical Labs.

According to information revealed by Monash University, the research will include growing 800,000 brain cells in a dish that are then taught “goal-directed tasks”. This research follows the announcement that the team last year taught the cells to play the game “Pong”.

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The research is important, according to Associate Professor Razi, because it will enable machines to undergo “continual lifelong learning”. This will ensure that technology can assimilate new information without biasing old information while conserving resources.

The associate professor explained that this is currently beyond the scope of modern AI.

He explained that the synthesis of lab-grown brain cells with AI will create “programmable biological computing platforms”.

“This new technology capability in future may eventually surpass the performance of existing, purely silicon-based hardware,” he said.

The outcomes of such research would have significant implications across multiple fields such as, but not limited to, planning, robotics, advanced automation, brain-machine interfaces, and drug discovery, giving Australia a significant strategic advantage.

“We will be using this grant to develop better AI machines that replicate the learning capacity of these biological neural networks. This will help us scale up the hardware and methods capacity to the point where they become a viable replacement for in silico computing,” Associate Professor Razi said.

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