Computers might run on human cells in the future, new study

A study conducted by John Hopkins University suggests that biocomputers powered by human cells could be developed in the future, which falls within a research plan called “organoid intelligence.”

Thomas Hartung, a professor of environmental health sciences at the Johns Hopkins Bloomberg School of Public Health and Whiting School of Engineering, who’s leading the research, explained that biocomputing is an enormous effort of compacting computational power and increasing its efficiency to push past the current technological limits.

Hartung and his colleagues have been working with brain organoids, with 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,” said the scientist, “because you can start manipulating the system, doing things you cannot ethically do with human brains.”

In 2012, Hartung used cells from human skin samples that had been reprogrammed into an embryonic stem cell-like condition to start growing and assembling brain cells into functioning organoids.

Each organoid has 50,000 cells or roughly the same number as the nervous system of a fruit fly. He is now thinking of using these brain organoids to create a futuristic computer.

“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 as quoted on Science Daily.

Even though computers process calculations involve numbers and data that are faster than humans, brains remain much smarter in making complex logical decisions, like telling a dog from a cat.

Hartung said that it might take decades before organoid intelligence can power a system as smart as a mouse, by scaling up the production of brain organoids and training them with artificial intelligence, he foresees a future where biocomputers support superior computing speed, processing power, data efficiency, and storage capabilities.