  Over the last decade, artificial intelligence has found many applications
areas in the society. As AI solutions have become more sophistication and the
use cases grew, they highlighted the need to address performance and energy
efficiency challenges faced during the implementation process. To address these
challenges, there has been growing interest in neuromorphic chips. Neuromorphic
computing relies on non von Neumann architectures as well as novel devices,
circuits and manufacturing technologies to mimic the human brain. Among such
technologies, 3D integration is an important enabler for AI hardware and the
continuation of the scaling laws. In this paper, we overview the unique
opportunities 3D integration provides in neuromorphic chip design, discuss the
emerging opportunities in next generation neuromorphic architectures and review
the obstacles. Neuromorphic architectures, which relied on the brain for
inspiration and emulation purposes, face grand challenges due to the limited
understanding of the functionality and the architecture of the human brain.
Yet, high-levels of investments are dedicated to develop neuromorphic chips. We
argue that 3D integration not only provides strategic advantages to the
cost-effective and flexible design of neuromorphic chips, it may provide design
flexibility in incorporating advanced capabilities to further benefits the
designs in the future.
