Remember quantum computing in the cloud?

What happened to quantum computing in the cloud? I’m sure it’s still around, but I don’t receive the press releases that flooded in just a few years ago.

To recap, quantum computing has long been heralded as the future of computational innovation, poised to tackle problems that are currently intractable with classical computers. However, in recent years, the buzz surrounding quantum computing in the cloud has been overshadowed by the rise of generative AI and the utilization of GPUs.

This goes against what we were told. I remember listening to a conference presentation that traditional computing models would become a thing of the past. Quantum computing would be in our clouds, data centers, phones, and even our watches. I guess they figured out that the cooling system for a quantum-powered watch would be as large as a motorcycle. We could put it on a cart and roll it down the street as we go for coffee.

Yes, I know that dozens of quantum computing fanboys and girls are yelling at their screens right now. I’m not saying that this type of computing does not have value. I’m not saying that it will never be the future. But I am saying the allure of AI and the paperless processing power provided by GPUs have distracted us away from quantum.

A technology landscape driven by hype

In 2024, we’re witnessing an intriguing shift in the cloud space. Organizations are diverting their attention from quantum paradigms toward the tangible, immediate benefits of generative AI and GPUs. This reflects a prioritization of technologies that can deliver clear, immediate business value.

Generative AI, fueled by GPUs, has captured the tech world’s imagination. It rapidly creates content, simulations, and insights that can be applied across industries, from automating complex processes to designing new products. The allure lies in its ability to produce these outputs quickly and cost-effectively, which is critical in today’s rapid-fire business environment.

However, GPUs are not all that. As I’ve pointed out here many times, GPUs may be overengineering AI systems when commoditized CPUs would do just fine. Indeed, I see a future when GPUs won’t be discussed at all. Instead, they will just bake into AI architectures. I’m not sure why we focused so much on that part of AI architecture in the first place.

Quantum computing’s potential

Quantum computing, while promising, is still mainly in the realm of future potential. The industry is making strides towards more advanced qubits and increased stability. However, the practical utility of these advancements remains over the horizon for many organizations. This timeline, coupled with the steep learning curve and investment required, has positioned quantum computing as a slower-evolving technology compared to AI.

Moreover, the current quantum offerings, often accessed via cloud platforms, are still primarily experimental. They require specialized knowledge to leverage effectively, whereas GPUs integrated into cloud services can be readily used to scale existing AI operations with relatively lower barriers to entry.

Why are generative AI and GPUs so dominant? The answer lies in immediate applicability and results. Businesses today face pressures to innovate faster than ever. Generative AI not only aids in creating innovative solutions but also provides a competitive edge in real-time decision-making processes. It is a tool ready to be wielded, with clear ROI and application pathways that quantum computing has yet to establish fully.

Additionally, optimizing and operating quantum systems requires a level of sophistication that many companies aren’t prepared to handle. They understandably allocate resources to technologies that fit seamlessly into their existing workflows and deliver quick wins.

Still a vital technology

My take is that we have limited attention. Generative AI, including GPUs, has pushed quantum off our radar. I can name a dozen such technologies that suffered the same fate. Remember the metaverse?

Although quantum computing might be perceived as taking a back seat, it remains a crucial part of the future landscape for problem domains like cryptography, complex system simulations, or optimization problems. Ongoing research and development in quantum cloud computing promises groundbreaking changes.

In the tech marketplace, you only have a certain amount of time in the spotlight. All emerging technologies require a patient and strategic approach to integrate these breakthroughs effectively into business strategies.

Will quantum grow in market share in the cloud? I think quantum has proven its value, so it does not need to do that. However, it has not captured hearts and minds, which is another aspect of the adoption of emerging tech that we most often forget about.