A Canadian startup called Xanadu has built a new quantum computer it says can be easily scaled up to achieve the computational power needed to tackle scientific challenges ranging from drug discovery to more energy-efficient machine learning.

Aurora is a “photonic” quantum computer, which means it crunches numbers using photonic qubits—information encoded in light. In practice, this means combining and recombining laser beams on multiple chips using lenses, fibers, and other optics according to an algorithm. Xanadu’s computer is designed in such a way that the answer to an algorithm it executes corresponds to the final number of photons in each laser beam. This approach differs from one used by Google and IBM, which involves encoding information in properties of superconducting circuits. 

Aurora has a modular design that consists of four similar units, each installed in a standard server rack that is slightly taller

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On January 8, Nvidia CEO Jensen Huang jolted the stock market by saying that practical quantum computing is still 15 to 30 years away, at the same time suggesting those computers will need Nvidia GPUs in order to implement the necessary error correction. 

However, history shows that brilliant people are not immune to making mistakes. Huang’s predictions miss the mark, both on the timeline for useful quantum computing and on the role his company’s technology will play in that future.

I’ve been closely following developments in quantum computing as an investor, and it’s clear to me that it is rapidly converging on utility. Last year, Google’s Willow device demonstrated that there is a promising pathway to scaling up to bigger and bigger computers. It showed that errors can be reduced exponentially as the number of quantum bits, or qubits, increases. It also ran a

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