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The doors are wide open for an artificial intelligence chip that uses human brain tissue and is a candidate to replace the computers of the future.

Researchers at Monash University have developed a semi-biological artificial intelligence chip they call "DishBrain", in which they incorporate human and mouse brain cells into the design. If the research is successful, it could open entirely new doors for cutting-edge computer chips using artificial intelligence.
 The doors are wide open for an artificial intelligence chip that uses human brain tissue and is a candidate to replace the computers of the future.
READING NOW The doors are wide open for an artificial intelligence chip that uses human brain tissue and is a candidate to replace the computers of the future.

The human brain is an extraordinary thing. Scientific experiments have not only proven that human brain cells can learn faster than artificial intelligence, but some scientists are now using brain cells in the use of artificial intelligence chips, making them faster and more powerful than ever before.

Last year, researchers from Monash University developed a semi-biological artificial intelligence chip called “DishBrain” that incorporates human and mouse brain cells into the design. DishBrain was extremely promising, learning to play a version of Pong in just five minutes.

This project has recently received a $407,000 grant from Australia’s National Intelligence and Security Reconnaissance Research Grants Programme. Perhaps it will be possible to develop more advanced versions of DishBrain.

These programmable computer chips not only harness the power of artificial intelligence, but seamlessly blend it with the human brain’s biological computing. This is a step forward that could take computing far beyond relying on silicon-based hardware. At least that’s what most researchers believe.

If this research is successful, it could open entirely new doors for cutting-edge computer chips using artificial intelligence. It could also have implications in many areas, including robotics, planning, advanced automation, drug discovery, and brain-machine interfaces.

The researchers say they will use the grant to develop more advanced artificial intelligence machines that can mimic the learning capacity of biological neural networks.

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