Computers with human brain a ‘biocomputer’ powered by human brain cells could be a reality in the coming decade, US researchers have claimed.
Calling the technology “organoid intelligence”, a team from Johns Hopkins University noted that it will exponentially expand the capabilities of modern computing and create novel fields of study.
According to Thomas, Professor of environmental health sciences at the Johns Hopkins Bloomberg School of Public Health, computing and artificial intelligence which drove the technology revolution, have hit a ceiling. And biocomputing can help “push past our current technological limits,” he noted.
For nearly two decades, scientists have used tiny organoids, lab-grown tissue resembling fully grown organs, to experiment on kidneys, lungs, and other organs without resorting to human or animal testing.
Recently Hartung and team has been working with brain organoids, orbs the size of a pen dot with neurons and other features that promise to sustain basic functions like learning and remembering.
“This opens up research on how the human brain works,” Hartung said. “Because you can start manipulating the system, doing things you cannot ethically do with human brains.”
Hartung began to grow and assemble brain cells into functional organoids in 2012 using cells from human skin samples reprogrammed into an embryonic stem cell-like state. Each organoid contains about 50,000 cells, about the size of a fruit fly’s nervous system. He now envisions building a futuristic computer with such brain organoids.
Computers that run on this “biological hardware” could in the next decade begin to alleviate energy-consumption demands of supercomputing that are becoming increasingly unsustainable, Hartung said, in the paper published in the journal Frontiers in Science.
While “the brain is still unmatched by modern computers,” by scaling up production of brain organoids and training them with artificial intelligence, Hartung foresees a future where biocomputers support superior computing speed, processing power, data efficiency, and storage capabilities.