Merging human brain cells with AI to transform machine learning

Transforming machine learning.

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A new Monash University-led research will merge the fields of artificial intelligence and synthetic biology to create programmable biological computing platforms. Scientists will grow human brain cells onto silicon chips, with new continual learning capabilities to transform machine learning.

For this research, scientists received a grant of almost $600,000 AUD from the prestigious National Intelligence and Security Discovery Research Grants Program.

Scientists will grow around 800,000 brain cells living in a dish, then “taught” to perform goal-directed tasks.

Associate Professor Razi said, “This new technology capability may eventually surpass the performance of existing, purely silicon-based hardware.”

“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.”

Associate Professor Razi said“The project garnered funding from the prestigious Australian grant body because the new generation of applications of machine learning, such as self-driving cars and trucks, autonomous drones, delivery robots, intelligent hand-held and wearable devices, “will require a new type of machine intelligence that can learn throughout its lifetime.”

“This “continual lifelong learning” means machines can acquire new skills without compromising old ones, adapt to changes, and apply previously learned knowledge to new tasks—all while conserving limited resources such as computing power, memory, and energy. Current AI cannot do this and suffers from “catastrophic forgetting.”

The research aims to cultivate human brain cells in the DishBrain system, a laboratory dish, to comprehend the numerous molecular principles behind lifelong constant learning.

Associate Professor Razi said, “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.”

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

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