Abstract

We are still years away from large-scale, fault-tolerant quantum computers, and the path to widespread adoption is not obvious. The vision is one of general, hybrid computing in the cloud capable of massive impact in a number of areas. Quantum computers are not magical, though: classical computing, powered by AI, will still be handling most of the tasks. While it’s not clear which areas will see the first big benefit from quantum computers, the strengths of quantum computers naturally lend themselves to quantum-centric problems, such as problems in chemistry. Identifying these problems and achieving real-world impact is an important milestone, key for avoiding a “quantum winter.” Do we need to wait for fault-tolerant machines for this to happen? Today we can build the workflows that will make use of quantum computers later on, and in fact even without quantum computers there are still a lot of interesting use cases that can be tackled with pre-quantum resources. We should also take a broader view of quantum technologies: in other domains, like sensing, quantum technologies can be deployed for real-world use cases today. In this talk I will discuss all of these issues, including examples, along with some of the challenges that remain in the path toward widespread adoption of quantum technologies. I will also compare the quantum path with that of AI, which, especially given recent progress in Generative AI, offers a few lessons. Ultimately, these paths will merge and lead to our next generation of high-impact technologies.