Quantum Computing Meets Artificial Intelligence: Innovations and Challenges

Abstract

With Quantum Computers being more accessible than ever, Artificial Intelligence (AI) researchers are keen to experiment with this computation power with the expectation to take the field to a new level. Exploiting the High dimensional Quantum Hilbert space to efficiently map the data features is the secret to achieve speedup. Furthermore, quantum entanglement is an exclusive feature of the Quantum platform, with a very high computation cost to be simulated classically, which has been experimentally proven to improve classification task accuracy and speed. Quantum Artificial Intelligence Software Engineering has its own challenges. Since the entire solution stack is different than its classical counterpart and the underlying hardware is vulnerable to noise, there is no methodology for producing and sustaining Quantum software as an emerging technology. Besides, an additional error mitigation process should be considered in the software life cycle to correct the defective results. Despite all the limitations of the Noisy Intermediate Scale Quantum (NISQ) hardware, many research projects are currently depending on it to solve problems like slowing down climate change, creating a sustainable business environment, and accelerating drug discovery. In this chapter, quantum-assisted artificial intelligence applications are discussed, highlighting their motivations as well as their challenges.