Updated at 18:30 EST to correct timeline of prediction to 2030 from 2020

Reverse-engineering the human brain so we can simulate it using computers may be just two decades away, says Ray Kurzweil, artificial intelligence expert and author of the best-selling book The Singularity is Near.

It would be the first step toward creating machines that are more powerful than the human brain. These supercomputers could be networked into a cloud computing architecture to amplify their processing capabilities. Meanwhile, algorithms that power them could get more intelligent. Together these could create the ultimate machine that can help us handle the challenges of the future, says Kurzweil.

This point where machines surpass human intelligence has been called the "singularity." It's a term that Kurzweil helped popularize through his book.

"The singular criticism of the singularity is that brain is too complicated, too magical and there's something about its properties we can't emulate," Kurzweil told attendees at the Singularity Summit over the weekend. "But the exponential growth in technology is being applied to reverse-engineer the brain, arguably the most important project in history."

For nearly a decade, neuroscientists, computer engineers and psychologists have been working to simulate the human brain so they can ultimately create a computing architecture based on how the mind works.

Reverse-engineering some aspects of hearing and speech has helped stimulate the development of artificial hearing and speech recognition, says Kurzweil. Being able to do that for the human brain could change our world significantly, he says.

The key to reverse-engineering the human brain lies in decoding and simulating the cerebral cortex – the seat of cognition. The human cortex has about 22 billion neurons and 220 trillion synapses.

A supercomputer capable of running a software simulation of the human brain doesn’t exist yet. Researchers would require a machine with a computational capacity of at least 36.8 petaflops and a memory capacity of 3.2 petabytes – a scale that supercomputer technology isn’t expected to hit for at least three years, according to IBM researcher Dharmendra Modha. Modha leads the cognitive computing project at IBM's Almaden Research Center.

By next year, IBM's 'Sequoia' supercomputer should be able to offer 20 petaflops per second peak performance, and an even more powerful machine will be likely in two to three years.

"Reverse-engineering the brain is being pursued in different ways," says Kurzweil. "The objective is not necessarily to build a grand simulation – the real objective is to understand the principle of operation of the brain."

Reverse engineering the human brain is within reach, agrees Terry Sejnowski, head of the computational neurobiology lab at the Salk Institute for Biological Studies.

Sejnowski says he agrees with Kurzweil's assessment that about a million lines of code may be enough to simulate the human brain.

Here's how that math works, Kurzweil explains: The design of the brain is in the genome. The human genome has three billion base pairs or six billion bits, which is about 800 million bytes before compression, he says. Eliminating redundancies and applying loss-less compression, that information can be compressed into about 50 million bytes, according to Kurzweil.

About half of that is the brain, which comes down to 25 million bytes, or a million lines of code.

But even a perfect simulation of the human brain or cortex won't do anything unless it is infused with knowledge and trained, says Kurzweil.

"Our work on the brain and understanding the mind is at the cutting edge of the singularity," he says.

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Photo: A graphic overlay shows neural connections on a scan of IBM researcher Dharmendra Modha's brain/IBM