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A Human Brain Is 30 Times More Powerful Than The Mightiest Supercomputer

The human brain is around 30 times more powerful than the world’s most advanced supercomputer, new research suggests. At this stage, we are very far away from Ultron-style machines to outsmart our brain.

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However we might attempt to mimic pieces of human characteristics to create advanced devices, we will not ever be able to match them completely. The camera cannot rival with the human eye, nor can the computer with the human mind. A new study thus shows that the human brain is much more powerful that the world’s most sophisticated supercomputers. In fact, the latter are only one-thirtieth as good as the brain.

The conclusion was reached by two PhD students (Katja Grace and Paul Christiano) in the US. They used the measurement called traversed edges per second (or TEPS) to calculate computational capability, that is, how fast can a computer shift data from one point to another, all within its own system. They used a rough estimate of this measurement’s equivalent in humans: how often neurones fire off electrical signals in the brain.

“A big pragmatic benefit of measuring the brain in terms of communication is that it hadn’t been done before,” said one of the authors, Katja Grace from the University of California, Berkeley in a statement to IEEE Spectrum. “[This method] provides a relatively independent estimate of the price of computing hardware roughly comparable to the brain.”

The team made use of the IBM Sequoia supercomputer as the Artificial Intelligence (AI) champion, the most powerful of computers on Earth.

Their results demonstrated that the human brain is at least as agile and up to 30 times faster than the Sequoia at shifting data.

“We have very little idea how efficiently the brain uses its computational resources, and how that will compare to the efficiency of systems that humans design,” says Grace. “So even if we knew how much hardware was needed to do what the brain is doing in the way the brain is doing it, this might be very different from the amount of hardware human engineers need to achieve the same functions once they have any way to achieve those functions.”

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