Quantum AI, the combination of artificial intelligence and quantum computing, aims to leverage the unique capabilities of quantum systems to enhance AI algorithms and solve complex problems beyond the reach of classical computing.
A new public report finds immense potential for the combined use of AI and quantum computing (QC). The report from the Quantum Economic Development Consortium (QED-C) found that QC and AI can complement and assist each other in significant and multidirectional ways. Quantum Economic Development Consortium Members include IBM and NVIDIA.
For instance, the report reveals that AI can help QC with error correction, while QC can help AI analyse complex models. Use cases include chemistry, logistics, energy, and environmental modelling.
The report studied the intersection of quantum and AI in four distinct categories:
- Novel solutions or applications that could emerge from the synergy of QC and AI that are currently not feasible with classical computing approaches
- Approaches for which AI could be used to identify use cases for QC
- Opportunities to use AI technologies to accelerate the development of specific QC technologies or the quantum ecosystem at large
- The technical advances needed for QC + AI integration in possible areas of their joint application.
For example, AI could help QC by accelerating the development of circuit design, applications, and error correction, while QC could help AI models analyse complex patterns and perform computations that are impossible for classical computers. In addition, a hybrid approach could leverage the strengths of both technologies to reduce algorithm complexity.
The report found that novel QC + AI approaches would be especially beneficial in chemistry, materials science, logistics, energy, and environmental modelling. For instance, QC + AI could be used to better predict high-impact weather events, giving residents, first responders, and governments more time to prepare for disaster response.
AI-enabled QC algorithms could also improve the precise modelling of chemical reactions, potentially leading to advances in pharmaceuticals. They could also help with logistics and energy storage through smart grid optimization and the optimization of shipping and airline routes.
In addition, the report signalled that QC could learn lessons from the adoption of AI, particularly with benchmarking and in anticipating privacy concerns.
The report makes three recommendations to increase the viability and adoption of QC +AI technologies:
- Include support for QC + AI in federal quantum and AI initiatives.
- Increase QC + AI research and education in academia.
- Connect industries from both sectors to accelerate QC + AI technology development, demonstration, and adoption.
