Quantum Computing is Closer Than You Think—And It Might Not Depend on Nvidia GPUs

SBS Swiss Business School > CSCFS News > Foresight > Quantum Computing is Closer Than You Think—And It Might Not Depend on Nvidia GPUs

On January 8, Nvidia CEO Jensen Huang made waves by predicting that practical quantum computing remains 15 to 30 years away, while also suggesting that Nvidia GPUs will be essential for implementing error correction. Yet, history is filled with brilliant minds misjudging the pace of technological progress. Huang’s claims not only underestimate the speed at which quantum computing is advancing but also overstate the role Nvidia’s hardware will play in that future.

Quantum computing is rapidly converging on utility. Google’s Willow device has already demonstrated that errors can be reduced exponentially as the number of qubits increases. It completed a benchmark test in under five minutes that would take a classical supercomputer an inconceivable 10 septillion years. While Willow remains too small for commercial applications, it has proven that quantum supremacy and fault tolerance are within reach. Meanwhile, companies like PsiQuantum are building large-scale quantum systems capable of solving real-world problems, set to enter commercial service before the end of this decade—without relying on Nvidia hardware. Instead, these machines use custom-built photonic architectures, operating at speeds far beyond what is achievable with GPUs.

At the same time, quantum algorithms are improving at a rate that outpaces hardware advancements. A collaboration between Boehringer Ingelheim and PsiQuantum recently demonstrated a 200-fold improvement in quantum simulations for drug discovery. Similarly, Phasecraft has pushed quantum-enhanced materials simulations to the brink of surpassing all classical methods. These developments suggest that quantum computing will soon be indispensable for solving problems that classical computers—even those powered by AI—cannot address.

The urgency for quantum computing stems from a fundamental limitation in how we currently understand the physical world. Our best classical computational methods fail to capture quantum interactions accurately, leaving massive gaps in fields like chemistry and materials science. Today, we lack an understanding of the precise mechanisms behind some of our most critical drugs, the behavior of superconductors, or even why certain simple materials exhibit extraordinary magnetic properties. The reality is that much of our modern scientific and industrial progress has relied on trial and error, rather than true mastery of the underlying quantum mechanics.

While AI has made remarkable progress in assisting scientific discovery, it remains constrained by the quality of its training data. DeepMind’s GNoME, for example, has identified hundreds of thousands of potential new materials using AI, yet it still depends on density functional theory (DFT)—a method that fails for complex quantum systems. No amount of AI-enhanced simulation can overcome the fundamental limitations of classical approaches when modeling quantum phenomena. Only a fully realized quantum computer will allow us to design materials with properties we can barely imagine today.

For years, skeptics assumed that quantum computers would remain error-prone and impractical for meaningful applications. That assumption is now crumbling. With large-scale quantum machines on the horizon and breakthrough quantum algorithms accelerating progress, we are transitioning from an era of discovery to one of deliberate design.

The implications are profound. Imagine a world where we no longer have to search for better materials, but can instead engineer them from first principles. Where drug discovery is no longer constrained by computational approximations, but driven by precise quantum simulations. Where the constraints of classical computing no longer limit our ability to understand and shape the world.

Jensen Huang may believe that quantum computing is decades away, but the reality suggests otherwise. The revolution is happening now, and when it arrives, it will reshape science, industry, and our understanding of the universe itself.