  Neuroscience and neurotechnology are currently being revolutionized by
artificial intelligence (AI) and machine learning. AI is widely used to study
and interpret neural signals (analytical applications), assist people with
disabilities (prosthetic applications), and treat underlying neurological
symptoms (therapeutic applications). In this brief, we will review the emerging
opportunities of on-chip AI for the next-generation implantable brain-machine
interfaces (BMIs), with a focus on state-of-the-art prosthetic BMIs. Major
technological challenges for the effectiveness of AI models will be discussed.
Finally, we will present algorithmic and IC design solutions to enable a new
generation of AI-enhanced and high-channel-count BMIs.
