Generative AI Through CAS Lens: An Integrated Overview of Algorithmic Optimizations, Architectural Advances, and Automated Designs

Generative artificial intelligence (GenAI) has emerged as a pivotal focus in global innovation agendas, revealing transformative potential that extends beyond technological applications to reshape diverse societal domains. Given the fundamental dependency of GenAI deployment on circuits and systems (CAS), a co-evolutionary approach integrating both technological paradigms becomes imperative. This synergistic framework confronts three interrelated challenges: 1) developing deployment-ready GenAI algorithms, 2) engineering implementation-efficient CAS architectures, and 3) leveraging GenAI for autonomous CAS designs - each representing critical innovations vectors. Given the rapid advancement of GenAI-CAS technologies, a comprehensive synthesis has become an urgent priority across academia and industry. Consequently, this timely review systematically analyzes current advancements, provides integrative perspectives, and identifies emerging research trajectories. This review endeavors to serve both AI and CAS communities, thereby catalyzing an innovation feedback loop: GenAI-optimized CAS architectures in turn accelerate GenAI evolution through algorithm-hardware co-empowerment.