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Like when the world transitioned from computer processors to graphics processors, we are currently witnessing another paradigm shift in which quantum computing is emerging from the shell of research and development to the forefront of mainstream technology. A McKinsey report published recently sheds light on the state of quantum technology today.
As per the report, quantum technology start-ups, which include companies in the domain of quantum computing, communications, and sensing, received an investment of $2.35 billion from investors in 2022. This amount exceeded the record for the highest annual level of investment in quantum technology start-ups, set in 2021. Moreover, four of the biggest deals in the 2000s closed in 2022.
However, the report also highlights that more investments are going into established startups than to new companies. Numbers show that only 19 quantum technology startups were founded in 2022 compared with 41 in 2021, bringing the total number of start-ups in the quantum technology ecosystem to 350.
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One of the companies that recently raised $24M in Series A funding is Strangeworks. Strangrworks is a software company that provides a cloud-based platform for developers, researchers, and enterprises to access and use advanced computing resources, like quantum simulators and quantum hardware.
Quantum becoming mainstream
William Hurley, Founder & CEO of Strangeworks, identifies two industry trends when it comes to providing scalable quantum solutions. First is the development of hybrid classical-quantum computing systems, which combine the strengths of classical and quantum computing to solve problems more efficiently, which can be useful for tasks such as optimisation problems or machine learning tasks.
The second trend involves the development of software tools and platforms that enable organisations to manage and scale their quantum computing resources efficiently. These tools include schedulers and optimizers for quantum computations, as well as resource and data management tools across multiple quantum computing platforms.
The case for a hybrid classical-quantum computer was also made by Timothy Costa, Director of HPC & Quantum at Nvidia, who told AIM, “while today’s QPUs are not capable of providing advantage in production applications, GPU supercomputers are time machines allowing researchers to work on future quantum systems that may accelerate critical workloads.”
At GTC 2023, Nvidia generated buzz when it announced a new system called the DGX Quantum system, developed in collaboration with Quantum Machines. The system will utilise the newly open-source CUDA Quantum open-source software.
Before you assume that a hybrid system involves mixing bits and qubits, Costa explains that this is not the case. The hybrid system operates by exposing familiar programming models, compilers, and toolchains for each type of accelerator, making it easy for domain scientists to map tasks to the processor (quantum or classical) that is best suited for the job. As a result, work is divided into discrete tasks that can be mapped to the processor of choice.
“For quantum computation, domain scientists describe tasks for the processor at a high level, and the compilation toolchain lowers this to a representation that the quantum processor can readily understand and execute,” adds Costa.
Apart from the technical challenges that arise when scaling up quantum systems for practical applications, Hurley highlighted the lack of available talent with expertise in both quantum and traditional computing as one of the biggest bottlenecks to quantum adoption. While the McKinsey report provides some cause for celebration, the overall situation remains grim.
The report states that the talent gap narrowed in 2022 compared to 2021, partly due to more academic institutions integrating quantum into their curriculum. According to their analysis, the remaining jobs could be filled by graduates from fields related to quantum technologies, which produce approximately 350,000 master’s-level graduates worldwide each year.
There are significant investments in programs related to critical subjects in quantum computing. “Despite the industry not experiencing significant growth, thousands of students and engineers are investing in certification courses to upskill themselves in areas related to quantum technology,” L Venkata Subramaniam, IBM Quantum India Leader, had told AIM.
The transition to quantum computing is expected to create four central job opportunities: hardware (building quantum computers), middleware (interconnecting hardware and software), research (developing algorithms that can run on today’s quantum computers), and data scientists or application developers (coding on top of the application layer).
However, Subramaniam believes that for those interested in hardware, the path is more challenging. According to him, picking up these concepts from online self-learning is difficult, and university courses are limited.