"After AI Comes This": Jensen Huang Pinpoints Quantum Computing... 'Early Commercialization' Begins This Year

Quantum computing is transitioning out of the laboratory and entering the ‘early commercialization’ phase, where it is being applied to real-world industries. In the financial markets, there is analysis that the quantum computing industry has moved beyond the simple proof of concept (PoC) stage, and that in some sectors, it has reached the ‘quantum advantage’ phase, surpassing classical computers.

Yonhap News Agency

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According to KB Securities on April 17, researcher Kim Se-hwan recently stated in a report, “The quantum computing industry has entered a commercial trajectory as of 2026, with 2029 being the key inflection point.”

The biggest obstacle for quantum computing thus far has been the ‘error rate’. This is because quantum states are highly unstable, making errors easy to occur during calculations. NVIDIA addressed this issue with its ‘NVQLink’ technology, which connects quantum processing units (QPUs) and graphics processing units (GPUs) with ultra-low latency. In this structure, the GPU corrects errors generated by the quantum computer in real time during calculations.

In addition, NVIDIA has released its open-source quantum artificial intelligence (AI) model ‘Ising’. The calibration process for quantum processors, which previously took several days, has been reduced to just a few hours, significantly increasing the feasibility of actual service applications.

Jensen Huang, CEO of NVIDIA, explained, “AI will serve as the operating system for quantum computers,” and added, “It can transform vulnerable qubits into scalable and reliable systems.” Sam Stanwyck, NVIDIA’s quantum product director, also stated, “Calibration and decoding are the biggest bottlenecks in scaling quantum systems,” and noted, “Our goal is for AI to support quantum circuit design and optimization in the future.”

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Ultimately, there is analysis that a ‘hybrid architecture’-combining quantum computers with GPUs-has established itself as the practical solution for commercialization.

Changes are also being detected in terms of the efficiency of quantum computing. Alan Baratz, CEO of D-Wave Quantum, emphasized that his company’s quantum computers operate on just about 10 kW of power, explaining, “They can run on the power equivalent to five to ten GPUs, reducing the power burden on AI data centers.”

Leading related beneficiaries include NVIDIA, IonQ, Rigetti, and Infleqtion. IonQ plans to unveil a 256-qubit system using a semiconductor-based manufacturing process within this year, and is also expanding its quantum networking business through a USD 7.5 million partnership with the University of Maryland.

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Researcher Kim advised that the current stock price level relative to future growth potential should be considered a key variable. He pointed out, “Based on enterprise value adjusted for growth potential, IonQ’s burden is lower than the market average, while D-Wave Quantum and Rigetti need to further secure visibility on additional revenue growth.”

However, there are clear risks that investors should be aware of. Researcher Kim noted, “Most pure quantum computing companies are currently running deficits, reflecting the industry’s inherent characteristic of requiring large-scale research and development (R&D) investment before commercialization.”

In particular, the realization of a ‘universal quantum computer’ that can be applied to all industries is expected to come after 2029. Until then, it is highly likely that the technology will continue to be used in a limited fashion within select industries.

Ultimately, while quantum computing is passing an important technological turning point, it is important to keep in mind from an investment perspective that it is an industry where it will take time for tangible results to become visible.

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