Neuromorphic Computing
Definition
Neuromorphic data processing is oriented on properties of biological nervous systems.
Computer architectures and algorithms that emulate properties of biological nervous systems such as event-driven, parallel processing.
Simply explained
Special computers imitate certain working methods of nervous systems, such as many simultaneous reactions to events.
Why it matters in practice
Helps realistically assess model quality, limits, and technical decisions.
Example from business
An event-based sensor processes changes energy-efficiently directly on special hardware.
Limits and pitfalls
- Exaggerate biological similarity or underestimate software and hardware ecosystems.
Origin & history
Carver Mead coined the term in the late 1980s.
Use in mid-sized companies
- Possible example: An event-based sensor processes changes energy-efficiently directly on special hardware.
Frequently asked questions
What does Neuromorphic Data Processing mean?
Computer architectures and algorithms that emulate properties of biological nervous systems such as event-driven, parallel processing.
Which mistakes should be avoided?
Exaggerate biological similarity or underestimate software and hardware ecosystems.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no proof of real customer results.
Editorially reviewed on: