There are more eyes on quantum computing (QC) today than there were on generative AI the day before ChatGPT was released in November 2022. This should give everyone pause as to what is possible for QC in 2025. Let’s dive in.
Investments in Agentic AI and Efforts to Further Develop QC Reveal Two Very Different Paths
Agentic AI and QC have dominated headlines in the early days of 2025. On one side, there is widespread agreement that 2025 is already the year of agentic and physical AI. On the other, skepticism persists regarding QC’s ability to become both commonplace and profitable anytime soon—especially after NVIDIA CEO Jensen Huang’s statement at CES 2025 that “very useful” quantum computing is still 20 years away.
Yet, both perspectives face their detractors. Prominent AI experts like Gary Marcus and Rodney Brooks have argued that AI’s short-term potential is overhyped and its ROI elusive, criticisms that remain relevant in 2025. This is why agentic AI has gained traction: it narrows the scope of AI applications, focusing on targeted tasks to maximize gains from current technology rather than striving for more ambitious general AI. Conversely, several QC providers have challenged Huang’s prediction of a 20-year timeline for useful QC. They assert that QC is already commercially viable for specific operations and that work toward broader applications continues steadily. D-Wave Quantum CEO Alan Baratz, for instance, declared that Huang is “dead wrong” about QC’s readiness. Furthermore, in an interesting move, NVIDIA announced its inaugural Quantum Day, slated for March 20 during GTC 2025, further underscoring its vested interest in QC.
This tension introduces both hope for accelerating QC advancements and added uncertainty regarding its timeline. Crucially, this uncertainty doesn’t necessarily indicate delay—it might suggest that breakthroughs could arrive sooner than expected.
There Is a Business and Technological Tension Between Traditional-Computing AI and QC
There is much to unpack here. First, Huang’s comments triggered a notable dip in quantum-related stocks, eliciting backlash from the QC community. Daniela Herrmann, co-founder of Dynex, a quantum-as-a-service company, told The Observer: “Huang’s extended timeline reflects the broader understanding of the challenges in achieving fully developed quantum systems, but it doesn’t fully acknowledge the progress being made by existing quantum-inspired applications.” The Observer further noted, “Hermann highlighted that Huang’s remarks seem to keep the spotlight on initiatives like NVIDIA’s CUDA-Q, which has yet to solve real-world problems at scale.”
Despite Huang’s cautious outlook, NVIDIA remains actively engaged in QC, primarily through collaborations and supportive technologies. NVIDIA’s CUDA software platform integrates with QC efforts, fostering a hybrid model that combines classical and quantum computing. At CES 2025, Huang stated, “Just about every quantum computing company in the world is working with us now… We’re extending CUDA to quantum, and they use us for simulating the algorithms, simulating the architecture, creating the architecture itself.” The intricate relationship between NVIDIA, classical-computing AI, and QC reflects a dynamic where Huang’s long-term prediction may coexist with evidence of tangible near-term progress.
A clear creative and competitive tension exists between traditional-computing AI, which currently commands billions in investments, and the potential of stable, scalable, multi-use QC. This interplay could generate the kind of entropy that resolves itself by accident, potentially catalyzing the singularity many are quietly hoping for.
The Quantum Singularity Is Unpredictable: It Could Take 20 Years; It Could Take 10 Months
The question on everyone’s mind is whether QC could experience an unexpected singularity in the short term, enabling the creation of stable, scalable, multi-use quantum computers. If this occurs, would it disrupt the entire AI industry, redirecting investments away from traditional GPUs toward the explosive promise of QC? A singularity represents a point where a groundbreaking, unforeseen technology emerges from ongoing efforts to refine existing systems. Just as ChatGPT took the world by storm in 2022, QC could similarly emerge as a transformative force, defying even expert predictions.
Just as the introduction of the transformer architecture by Google in 2017 shifted all timeline predictions about LLMs, a QC singularity represents that philosopher’s stone everyone envisions as decades away—until it suddenly hits, changing all predictions drastically.
As efforts to achieve QC accelerate, the prospect of a singularity grows increasingly plausible. Such a breakthrough could propel AI advancements of 2022–2024 into hyperdrive. With the world eager for artificial super intelligence (ASI), QC might be the only viable path to achieving it.
The Quantum Horizon: A Breakthrough Waiting to Happen
Despite skepticism, recent developments suggest that QC may be closer to a breakthrough than previously anticipated. IBM’s unveiling of its 1,121-qubit Condor processor demonstrates significant progress toward scalable quantum systems. This advancement, paired with improvements in quantum error correction, addresses critical challenges in the field. Plus, IBM continues to refine and expand its quantum software ecosystem, notably Qiskit, an open-source quantum computing platform that enables developers to design and run quantum algorithms. This platform is central to IBM’s vision of creating a robust quantum computing ecosystem that supports both researchers and industry professionals.
Similarly, Google’s Quantum AI division introduced the Willow chip, a 105-qubit processor capable of solving computational tasks previously deemed infeasible for classical supercomputers. These milestones highlight the rapid evolution of quantum hardware.
On the global stage, the European Union’s Quantum Flagship Program, launched in 2018 with a €1 billion budget over ten years, positions Europe as a leader in quantum technology. Concurrently, the U.S. National Quantum Initiative accelerates quantum research and development through coordinated federal efforts.
Private sector contributions are equally noteworthy. IonQ’s collaboration with NVIDIA to integrate QC with classical systems exemplifies practical applications emerging from these technologies. Rigetti Computing’s advancements in AI-powered calibration further demonstrate the industry’s momentum toward operational quantum solutions.
These developments parallel the unexpected rise of generative AI, suggesting QC could experience a similar rapid advancement. With substantial investments, international collaborations, and technological progress converging, the possibility of a QC singularity—where quantum systems achieve practical, widespread utility—appears increasingly plausible in the near future.