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Quantum computing staged a comeback earlier this month when Google announced a new chip called ‘Willow’ on the 9th of December. According to Google, the new chip allows it to perform an extremely complex mathematical task in just under 5 minutes, when it would have taken the most powerful supercomputer in existence today over 10 septillion years to complete. A septillion is equal to 1 followed by 24 zeros. It’s at a scale a human brain can’t even process. Certainly, an achievement that should change how computers today perform computation.
A quantum computer on a countertop in an engineering laboratory with a technician at work.
Despite the above progress, Nvidia’s Blackwell GPUs continue to be the hype. They’re the most powerful GPUs in existence today, but surely they should pale in comparison to what Google has achieved. In reality, Nvidia continues to stay relevant because quantum computing isn’t simply about replacing the chip on your laptop. Traditional laptops using CPUs and GPUs continue to be more efficient for general-purpose computing.
So how does Nvidia then benefit from the quantum computing revolution? Here are three ways Nvidia is a beneficiary, no matter who makes the best chips.
Quantum computers are extremely expensive to build. It is not possible to build quantum computers just to test if they can perform certain tasks. So a lot of simulation work is needed before something concrete can be built. That’s where Nvidia’s GPU comes in. The more powerful the GPU, the quicker it is to carry out the simulation and reach desired results.
Secondly, even when quantum computers do become the norm, they will always accompany traditional computers in a hybrid setting. This hybrid setting will once again require the best computers to support the quantum computers, requiring once again Nvidia’s GPUs, except in a support role.
Lastly, just like Nvidia dominates the GPU world thanks to its proprietary software, Nvidia continues to provide support for quantum computing software. The CUDA-Q platform provides developers with the resources to write code that can run on both quantum computers and classic GPUs. Through this software, Nvidia not only helps the development of quantum computing but also solidifies its economic moat by being the right software provider to bridge the gap between traditional and quantum computing.
In this way, Nvidia stands to gain a lot from quantum computing even though it doesn’t make quantum computing chips. That’s food for thought for the bears who thought Nvidia had peaked and sold all the GPUs it could sell. There’s more after AI!