Google’s quantum computing breakthrough with Willow at the end of last year, followed by advancements by both Microsoft and Amazon already this year, has prompted nearly every technology luminary to predict a timeline for practical quantum computing.

Nvidia CEO Jensen Huang was one of the first to weigh in on the quantum horizon. In January, he said that he believed practical quantum computing was still 15 to 30 years away, before recently walking back that timeline.

As one of the early investors in PsiQuantum, which recently announced it is already making millions of quantum computing chips, I believe it is more like two years when we enter the early innings of practical quantum computing applications. In fact, quantum computing is entering a phase in 2025 that mirrors where AI was roughly five years ago.

For a very long time before its breakthrough, many questioned AI’s feasibility. Yet, in the background, researchers and companies on the front lines were making exponential progress year-over-year on algorithms. Eventually, the hardware and computing power caught up with that progress, and everything aligned for takeoff. That same alignment is occurring now in quantum computing.

However, regardless of your prediction on the arrival of useful quantum computing, the truth is the technology industry desperately needs large-scale quantum computing to work—sooner rather than later—for two major reasons: we are approaching the end of Moore’s Law of classical computing, and AI is creating skyrocketing computational needs.

A ceiling on Moore’s Law beckons the next computing paradigm

Moore’s Law is the computing principle that the number of transistors in an integrated circuit doubles about every two years. We have been riding this wave for 30 or 40 years to achieve increasingly powerful computations. But we are approaching fundamental physical limits where you simply cannot squeeze more transistors into the same silicon chip indefinitely.

This is not just an incremental R&D challenge; the technology industry needs a step function or a revolutionary leap forward. We experienced a similar paradigm shift in the 1960s when the first digital CMOS chips emerged, catalyzing the formation of Silicon Valley with pioneers like Fairchild and Intel.

Quantum computing represents our best shot at the next computing paradigm. This explains why Google, Microsoft, Amazon and other tech giants are investing heavily in quantum research and development, as they recognize classical computing power is becoming the critical limiting factor for future technologies.

All our computing for the last 150 years has operated on a binary digital system where everything exists in one of two states: either a zero or a one. From the latest GPUs to the first microcontrollers, this fundamental limitation remains.

Quantum computing breaks this paradigm by allowing qubits to exist in multiple states simultaneously, to be both zero and one until measured. This approach exponentially increases information storage and computational capacity, creating a fundamentally different system rather than improving incrementally.

AI needs the computational power of quantum

Of course, the latest technology requiring the biggest use of the world’s computing power is AI. The Centre for the Governance of AI has found that over the past 13 years, the amount of compute used to train leading AI systems has increased by a factor of 350 million.

While specialized hardware architectures like GPUs continue to deliver significant performance gains, and algorithmic improvements and distributed computing offer more efficient ways to power AI, we will eventually reach classical limitations as the amount of compute required to train the most powerful models is increasing by around a factor of five each year.

As quantum computing arrives, I do not believe it will take over AI training entirely, but quantum processors will undoubtedly be able to take on some of the heavy load of computing by accelerating bottlenecks, such as finding optimal weights in large neural networks. It will also unlock entirely new AI architectures. While many dismiss quantum computing’s impact on AI because they cannot immediately envision quantum-powered consumer applications, it will enable more advanced reasoning capabilities in AI systems, which will then translate to consumer applications we can’t yet imagine.

Consider a parallel: when we were building 3G modems 25 years ago, sending data at 2 Mbps to phones with tiny 1.4-inch screens, nobody could anticipate services like Uber or live streaming on smartphones. First comes capability and then comes applications. Quantum will initially address AI’s computational bottlenecks, but consumer applications, particularly those for more sophisticated AI reasoning capabilities, will follow quickly.

From physics to engineering: the quantum inflection point

Quantum computing today stands where the semiconductor industry was in the late 1950s and early 1960s at the critical transition from physics to engineering. We are moving beyond theoretical discussions into practical implementation challenges. Just as the pioneers of Silicon Valley transformed theoretical semiconductor physics into manufacturable products, today’s quantum engineers are working to translate quantum mechanics from laboratory curiosities into reliable, scalable systems.

This transition represents the most exciting phase of any technological revolution. The fundamental scientific principles are established, and now we are solving the engineering challenges: error correction, qubit stability, scaling architecture and designing practical applications that leverage quantum advantage.

The companies that succeed in this transition in moving quantum from physics to engineering will define the next computing era, much as Intel shaped the microprocessor age. We are witnessing the birth of an industry that will fundamentally reshape computing capabilities across every sector.

As with previous technological revolutions, those who recognize this inflection point early will help shape the quantum future rather than merely adapting to it. Quantum’s arrival is really a question of when and not if, as the transition is already underway, and its answers to our current computing, AI and technological challenges will be profound.

By: DocMemory
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