Intel CEO Sees Quantum Computing Working Alongside CPUs and GPUs

Insider Brief

• Intel CEO Lip-Bu Tan said quantum computers are likely to operate alongside CPUs and GPUs as specialized systems for selected computing tasks.

• Tan said Intel is focusing its quantum work on error correction, practical applications and the business case for customers to pay for the technology.

• Quantum computing remains constrained by error rates, cryogenic cooling requirements and the need to scale hardware, even as Intel and the U.S. government continue to invest in the field.

• Image: Intel

I ntel Chief Executive Lip-Bu Tan said quantum computers are likely to work alongside conventional processors rather than replace them, as the industry searches for commercially useful applications.

“In my view, GPUs, CPUs and quantum computing are all forms of computing, so they will run together in certain application areas, and you will be able to use quantum computing more efficiently,” Tan said during a keynote conversation at Splunk’s .conf26 conference in Denver, according to Seoul Economic Daily .

Photonics quantum computing giant PsiQuantum recently appointed Tan to its Board of Directors .

The comments reinforce a view that quantum computing can fit within a broader computing stack that already relies on central processing units, or CPUs, and graphics processing units, or GPUs. CPUs handle a wide range of general-purpose tasks, while GPUs have become essential for training large artificial-intelligence models because they can perform many similar calculations at once.

Quantum computers could still find a place in that stack because they are designed for a narrower set of problems. They use qubits, which can represent quantum states that differ from the 0s and 1s used by ordinary digital bits. That property could eventually help researchers model molecules, materials and other complex physical systems that are difficult for conventional machines to simulate.

But quantum processors remain experimental, and they are not expected to replace CPUs or GPUs in mainstream computing. Most likely, conventional computers would prepare data, run surrounding software and check results, while quantum processors take on selected portions of a calculation.

Tan’s remarks come as Intel seeks to regain momentum in AI infrastructure while maintaining long-running research in quantum computing. Seoul Economic Daily reported that Tan covered a broad range of issues during the 30-minute session, including AI investment, chip supply constraints, the growing importance of AI inference and Intel’s manufacturing plans.

Inference is the stage in which a trained AI model generates an answer, recommendation or other output. It has become a growing focus for chip companies as businesses move from building AI models to running them in products and services.

A Long-Term Bet on Quantum

Tan raised quantum computing while discussing the need for companies to accept technological change rather than protect existing businesses.

“Sometimes companies tend to protect what they have rather than attempt disruptive change,” he said, as reported by Seoul Economic Daily . “In quantum computing, people also think the change is taking too long, but I have continued to invest in quantum computing.”

The field still faces major technical obstacles. Qubits are highly susceptible to interference from heat, vibration, radiation and electrical noise. Such disruptions can alter the fragile quantum information stored in a processor and introduce errors into calculations.

For that reason, many quantum systems use cryogenic equipment that cools chips to temperatures close to absolute zero. The cooling systems are large, complex and expensive, creating an engineering challenge for companies that hope to build larger machines.

Asked when quantum computing would become practical, Tan pointed to two central issues: making calculations more reliable and identifying customers willing to pay for useful systems.

“I am focusing now on error corrections and applications,” Tan said. “I also think about who is going to pay for it.”

Quantum error correction uses many physical qubits to protect a smaller number of more reliable logical qubits. The process is widely viewed as necessary for quantum computers to perform long, complex calculations, but it requires considerable hardware and control systems.

“There will be far more variations you can work with using qubits,” he added, Seoul Economic Daily reported. “To me, that is very interesting.”

Tan added that cryogenic infrastructure could remain an important constraint in the near term — over the next three to five years.

Intel Labs has pursued silicon spin qubits, an approach that uses the quantum properties of individual electrons in silicon devices. The company has bet that silicon could offer a potential manufacturing advantage because it draws on techniques related to the semiconductor industry.

Intel previously introduced its Tunnel Falls research chip to give academic researchers access to silicon spin qubits. It also unveiled Horse Ridge II, a cryogenic control chip designed to operate closer to quantum processors in ultra-cold environments.

Placing more control electronics near the qubits could reduce some of the wiring and engineering demands associated with large quantum systems. Still, researchers must demonstrate that those control components can operate without adding enough heat or electrical interference to undermine the qubits.

The industry has not agreed on a single hardware approach with companies pursuing superconducting circuits, trapped ions, neutral atoms, photonics, silicon spins and other methods, each with different strengths and scaling challenges.

Tan’s comments arrived as governments increase their focus on quantum technology as a strategic industrial and national-security priority. Its commercial potential is also being hotly debated at the national levels.

For example, President Donald Trump signed an executive order on quantum technology in June that directed federal agencies to update the national quantum strategy, support research and commercialization, strengthen domestic supply chains and develop plans for quantum sensing and networking.

The order also called for a national effort to develop a quantum computer capable of supporting scientific applications beyond the reach of current classical systems. It directed the Department of Energy to identify technical requirements for such a machine and to explore partnership models with the private sector.