Neuromorphic Computing

Explaining how Projected SNN Training will Largely Impact our Interactions with Technology

  • Elements Editor
  • Will Riherd


In the face of increasingly large computational demands and the impending halt to Moore's law, the semiconductor industry has been forced to re-evaluate the traditional computing paradism. Central to this re-evaluation has been the novel development of neuromorphic computing - an approach that, at its core, seeks to replicate the brain in silicon. Despite challenges on the algorithmic front, neuromorphic computing promises a massively parallel, efficicient, and scalable computational solution with large implications on the daily lives of consumers. The future of the technology, however, is uncertain. With the rise of high performance and Quantum computing as promising alternatives, te semiconductor industry at large must consider the extent to which neuromorphic computing can emerge as a viable and feasible solution in the coming years. It is vital, therefore, to understand the theoretical underpinnings of the neuromorphic approach and predict the likelihood of its implementation within the next decade

How to Cite
Elements, & Riherd, W. (2022). Neuromorphic Computing. Elements, 17(1), 33-40.