Tokyo and Broomfield, Colorado – January 29, 2025 – SoftBank Corp. and Quantinuum today announced a partnership in quantum computing intended to “unlock innovative quantum computing solutions that will overcome the limitations of classical artificial intelligence and realize next-generation technologies.”
SoftBank made major news last week at the White House, when President Trump said the Japan-based multinational investment holding company will be part of Stargate, a $500 billion effort to expand AI data center capacity in the U.S.
As for Quantinuum, the trapped-ion quantum company formed in 2021 by the merger of Cambridge Quantum and Honeywell Quantum Solutions, partnering with one of most prominent techology investors is a significant achievement.
In their announcement, SoftBank and Quantinuum said a hybrid approach to AI computing that combines CPUs, GPUs and quantum processing units (QPUs) “holds the potential to further extend the capabilities of AI. By leveraging the unique strengths of each type of processing unit, hybrid systems can execute more advanced and diverse computations, providing innovative solutions that surpass traditional limitations.”
They said that while AI is delivering impressive results, there are still significant challenges that AI alone is struggling to overcome, such as complex optimization problems, deciphering causal relationship analysis and conducting high-precision simulations based on fundamental equations.
On the quantum side, the companies said several technical and business challenges need to be addressed:
- Initial Investment and Operational Costs: The substantial initial investment and operational costs required for the development and deployment of quantum computers lack concrete cost recovery strategies, which in turn suppresses the drive for companies to develop and adopt the technology.
- Clarification of Revenue Models: The business models for generating revenue, including the methods of offering quantum computers and setting usage fees, have not yet been fully realized.
- Discovering Use Cases: There is a shortage of use cases that clearly demonstrate which fields quantum computers will be useful in. Understanding the market size and revenue models through clear examples, especially in areas such as quantum chemical calculations and machine learning, is necessary.
- Understanding the Market and Revenue Predictions: It is crucial to specifically identify the areas where computations can only be performed by quantum computers and are commercially viable, as well as to predict the timing and scale of these applications.
- Limitations and Challenges of Hardware: The current hardware performance (number of qubits and operation precision) of quantum computers is inadequate for handling practical problems, and significant enhancements in performance are needed for practical use.
- Software Development and Error Mitigation: The development of hybrid algorithms that combine traditional methods, as well as advancements in error suppression, mitigation, and correction technologies, are essential to enable practical computations. Furthermore, developing technologies that mutually complement hardware and software are also indispensable.
- Timing for Service Provision: Making decisions based on a deep understanding of technology to provide services at the optimal timing requires assessing the speed of technological advancements and market needs.
