Neuromorphic computing might be the answer to AI’s hardware problem.
The rise of machine learning and artificial intelligence is asking questions about what is the best way to build a computer, and approaches that derive inspiration from the brain could provide an answer. Here, in a series of articles, we explore what such neuromorphic computing can do.
Neuromorphic engineering attempts to create brain-like computing hardware and has helped reawaken interest in computer chip start-ups. But is the technology ready for mainstream application?
Neuromorphic engineering aims to create computing hardware that mimics biological nervous systems, and it is expected to play a key role in the next era of hardware development. Carver Mead recounts how it all began.
This Review Article examines the development of spintronic devices for neuromorphic computing, exploring how magnetic tunnel junctions and magnetic textures can act as artificial neurons and synapses, as well as considering the challenges that exist in scaling up current systems.
This Review Article examines the development of neuro-inspired computing chips and their key benchmarking metrics, providing a co-design tool chain and proposing a roadmap for future large-scale chips.
This Review Article examines the development of organic neuromorphic devices, considering the different switching mechanisms used in the devices and the challenges the field faces in delivering neuromorphic computing applications.
This Review Article examines the development of in-memory computing using resistive switching devices.