During an AI event at the White House, Melania Trump announced “the robots are here” and encouraged us all to treat them as we would treat our children.
But while the CEOs of tech giants and political courtiers gathered around the first lady to think about their new AI brood, China’s attention was elsewhere. The South China Post reported that Hong Kong’s research labs have been reorganised to support Beijing’s technology objectives, with a focus on quantum science.
Beijing has announced plans for increased investment in quantum research on multiple occasions. Earlier this year, researchers from USTC in China reported reaching a new milestone in quantum computing with the Zuchongzhi 3.0 processor by performing a 105-qubit random circuit sampling task. This task is considered infeasible for current classical supercomputers such as Frontier, which would require significantly more time to complete it.
Patent analysis also indicates that, in quantum computing, China produces a slightly higher volume of research publications than the United States, contributing 22.8 percent of global papers compared to the United States’ 21.3 percent. Albeit with the US recognised for leading in research quality buy a considerable margin.
China is also estimated to have higher investment figures, though official numbers are limited. Some estimates suggest that China has allocated $15 billion to quantum initiatives, while the United States has committed $7.7 billion.
This imbalance is problematic. Many western cybersecurity experts are concerned about falling behind in cryptography, while debate continues over whether AI or Quantum will drive the next digital era. It’s crucial to balance technology investment; AI investment is hoovering too much oxygen out of the room—to the detriment of Quantum.
Great post – the quantum angle is often the one that gets overshadowed when AI hogs all the headlines. China’s Zuchongzhi 3.0 milestone is impressive, but these ‘quantum supremacy’ demos don’t yet translate into practical tools. The real race is building stable qubits, scaling error correction, and finding useful algorithms – where the U.S. and Europe still punch above their weight (via IBM, Google, IonQ, Quantinuum, IQM, and others).
It’s also important to remember that quantum isn’t totally separate from AI. Future quantum computers might accelerate optimization, speed up sampling, or reduce training times for machine learning models. The danger now is that AI investments are sucking all the policy and funding oxygen out of the room, just as quantum is gearing up for serious gains.