The answer is often not what people want to hear. Here’s where quantum computing fits in the world of cloud computing, and perhaps in your business. Credit: Sakkmesterke / Getty Images You can google any number of confusing definitions of quantum computing. Simply put, quantum computers are machines that leverage the attributes of quantum physics to store data and perform computations. Clear as mud. The best way to understand the value of quantum computing—or lack thereof—is to understand the use case. Quantum computing can be advantageous for certain tasks where it can vastly outperform even supercomputers. It is typically associated with the following use cases: cybersecurity, pharmaceutical development, financial modeling, improving batteries, cleaner fertilizer, traffic optimization, weather forecasting, climate change, artificial intelligence, solar capture, and electronic materials discovery. Traditional computing can also solve these problems, certainly high-performance computing/supercomputers. So where does quantum computing enter the picture? Most of the vendors in the public cloud market have a quantum offering. In 2016, IBM stood up a quantum computer on its cloud. Since then, IBM has expanded its cloud-based quantum computing offering. Never to be outdone, Amazon has developed and launched its own quantum computing services, and Microsoft announced Azure Quantum, which provides quantum algorithms, hardware, and software. Of course, Google is a quantum player as well. Should you try it? That decision is really about matching use cases with quantum computing effectively. I suspect that quantum computing is not a good fit for accounting or inventory systems where the processing is more fine-grained and transactional. However, it’s sometimes a good option if you’re looking to take that accounting or inventory data and build complex financial models that are capable of predicting the future. Most of those use cases for high-performance computing may be better served by quantum computing, but not all of them. The trade-off is the cost compared to traditional computing, even high-performance computing in the cloud. Unless there is a compelling reason to leverage quantum computing for specific, purpose-built situations where there is a clear advantage, it’s perhaps not worth the extra cost and risk. Also, try finding quantum computing people who are willing to work outside of the universities. I’ve tried and failed the few times that I was involved in quantum projects. Quantum computing in the cloud is like any new technology. It starts out as a niche solution, typically with more cost and risk. We’re here now. Second, it’s leveraged for a small percentage of applications and data solutions. Finally, it becomes just another public cloud service offering: one that may have a bit of a cost premium, but a fraction of what it was back in 2021. Related content analysis Strategies to navigate the pitfalls of cloud costs Cloud providers waste a lot of their customers’ cloud dollars, but enterprises can take action. By David Linthicum Nov 15, 2024 6 mins Cloud Architecture Cloud Management Cloud Computing analysis Understanding Hyperlight, Microsoft’s minimal VM manager Microsoft is making its Rust-based, functions-focused VM tool available on Azure at last, ready to help event-driven applications at scale. By Simon Bisson Nov 14, 2024 8 mins Microsoft Azure Rust Serverless Computing how-to Docker tutorial: Get started with Docker volumes Learn the ins, outs, and limits of Docker's native technology for integrating containers with local file systems. By Serdar Yegulalp Nov 13, 2024 8 mins Devops Cloud Computing Software Development news Red Hat OpenShift AI unveils model registry, data drift detection Cloud-based AI and machine learning platform also adds support for Nvidia NIM, AMD GPUs, the vLLM runtime for KServe, KServe Modelcars, and LoRA fine-tuning. By Paul Krill Nov 12, 2024 3 mins Generative AI PaaS Artificial Intelligence Resources Videos