It seems for every proponent for quantum computing there is also a detractor. The detractors often refer to quantum computing as “a science project”, “hype”, “a hoax”, even a “failed cause”. If you look back through the history of the technology industry, it is littered with technologies that failed for various technical or business reasons. So, there is reason to be skeptical. However, there are just as many technologies that went on to chart the future direction of innovation because of major advancements that enabled the technology. Some have even had a similar level, if not more, of skepticism and of being “a science project” – technologies like artificial intelligence (AI). AI is a concept that had been theorized about long before the development of the first silicon transistor, but it wasn’t until the past decade that it became a reality through advancements in silicon technology, processing architectures, and deep learning techniques. Similarly, quantum computing technology is real now and is on the verge of that breakout over the next decade.
Quantum Computing Is Not Easy
Even describing the concept of quantum computing is not easy. Classical computers use bits to represent a one (on state) or zero (off state), while quantum computers use qubits that can represent multiple states through superposition and links with other qubits through entanglement. The result is a computer that scales exponentially in terms of compute capacity. While this makes quantum computers ideally suited for large mathematical models, they are not suited for handling the simple overhead tasks associated with computing. As a result, quantum computing is better positioned as a new accelerator technology, similar to a Graphics Processing Unit (GPU), Digital Signal Processor (DSP), or Field-Programmable Gate Array (FPGA), but on a much larger scale in terms of computing performance. However, quantum computers require specialized control logic and memory because of the unique compute architecture on which quantum computing is based. Large refrigeration units are also required because they operate at near absolute zero, meaning zero degrees Kelvin or -273.15 degrees Celsius.
Rapid Advances In Quantum Computing
If quantum computing is so fraught with challenges, the natural question is why do I think that we are on the cusp of major advances in quantum computing? One of the reasons is the level of investment in quantum computing. The benefits of having a single computer that can outperform many supercomputers is so valuable that the scientific community, technology industry, governments, and enterprises are investing billions into the development and use of quantum computing. This includes industry leaders like Alibaba, Amazon, IBM, Intel, Google, Honeywell, Microsoft, Nvidia, and Toshiba among many other companies. Likewise, the US Government has a National Quantum Initiative to “accelerate quantum research and development for the economic and national security of the United States.” A key example of this investment is evident walking through the IBM quantum data center in Poughkeepsie, New York, which I had the opportunity to tour earlier this year.
Another reason is the continued advancements being made in quantum computing is improvements in quantum chips, control logic, systems, and software. These advancements are especially true of the development tools for error mitigation, suppression, and correction. As an example, IBM holds the lead in quantum scaling with the 433-qubit Osprey processor introduced in 2022 and is slated to introduce the 1,121-qubit Condor processor later this year. If you consider IBM’s quantum processor roadmap, the number of qubits will increase by approximately 2-3x every year. IBM is also networking quantum computers together to further increase the qubit capacity. IBM has stated that it has a goal of 100,000 qubit systems by 2033. Industry and academia are already working on practical applications with current quantum computers. This development will accelerate as qubit capacity increases in the latter half of this decade.
The final reason, and the one I believe will be critical to the next step in quantum computing, is artificial intelligence (AI). Thus far, the focus has been integrating classical computers with quantum computers. However, AI holds the potential to both improve the capabilities and performance of quantum computers and being improved by quantum computers but the work in this area is just beginning.
Quantum Timeline
When and how will quantum computing become available for practical applications? With thousands of universities, research organizations, and enterprises already learning and experimenting with quantum computing, the answer is now, for some limited applications. As published in the scientific journal Nature, IBM partnered with US Berkley to demonstrate the ability of quantum computers with just 127 qubits to outperform classical computers in material modeling. However, IBM believes that the 100k qubit capacity level will drive an inflection point for the industry. With quantum systems networked together, this threshold is rapidly approaching.
The Quantum Era
Given the amount of quantum computing investment, advancements, and activity, the industry is set for a dynamic change, similar to that caused by AI – increased performance, functionality, and intelligence. This also comes with the same challenges presented by AI, such as security, as outlined in the recent Quantum Safe Cryptography article. But just like AI, quantum computing is coming. You might say that quantum computing is where AI was in 2015, fascinating but not widely utilized. Fast forward just five years and AI was being integrated into almost every platform and application. In just five years, quantum computing could take computing and humanity to a new level of knowledge and understanding.