Skip to main content

Google has poached an expert scientist to build a quantum computer

Google has poached an expert scientist to build a quantum computer


John Martinis and his team join the Quantum Artificial Intelligence Lab

Share this story

Google has hired a team of quantum computing experts from University of California Santa Barbara as part of a drive to design and build new quantum processors based on superconducting electronics. Noted physicist John Martinis and his team will join Google's Quantum Artificial Intelligence Lab (QuAIL), alongside representatives from NASA and the Universities Space Research Association.

Tests showed quantum computers may be no faster than regular computers

Quantum computing was fêted as the next step in computing technology, with quantum processors able to work out calculations in short periods of time that would take regular computers millions of years. But the technology took a hit earlier this year when tests on the world's first commercially available quantum computer — the D-Wave 2, priced at around $15 million — appeared to show that it was no faster than a standard computer. Tempering that discovery is a healthy debate about whether the D-Wave 2 is actually a quantum computer or not.

Last October Martinis called attempting to manufacture an actual quantum computer "a physics nightmare," but the acquisition of the physicist and his team for QuAIL shows that Google has not given up on the technology. Together with the work of AI specialists DeepMind, acquired by Google in January this year, quantum computing might help us create the first sentient robots.

The company likely won't be able to turn out its first home-grown quantum computer for a few years at least, but its power could incredible. The Financial Times says it would take "a bank of computers the size of North America running for 10 years and consuming the earth's entire store of energy every day to figure out all the prime numbers contained in a 2,000-long sequence of binary code." A quantum computer the size of a lecture theater could theoretically manage it in 24 hours.