10 interview questions and answers on Neuromorphic Computing

Here’s a list of questions and answers about the Neuromorphic Computing. This guide can help you prepare for job interviews for Neuromorphic Computing skill requirements.

List of 10 Neuromorphic Computing Questions and Answers

Question 1: Define neuromorphic computing.

Answer 1: It’s a computing paradigm that mimics the biological neural structure and operation of the brain.

Question 2: What are spiking neural networks (SNNs)?

Answer 2: SNNs model neurons that communicate via discrete spikes, enabling brain-like information processing.

Question 3: Name a neuromorphic chip developed by Intel.

Answer 3: Intel Loihi.

Question 4: How does neuromorphic hardware differ from traditional CPUs?

Answer 4: It operates asynchronously, consumes less power, and supports event driven processing.

Question 5: What is synaptic plasticity in neuromorphic systems?

Answer 5: It refers to the dynamic adaptation of synaptic weights, mimicking learning in biological systems.

Question 6: Mention one key advantage of neuromorphic computing.

Answer 6: Ultra low power consumption for real time pattern recognition.

Question 7: What is IBM’s contribution to neuromorphic computing?

Answer 7: IBM developed the TrueNorth neuromorphic chip with a million neurons.

Question 8: What is the use of memristors in neuromorphic design?

Answer 8: Memristors can act as synapses, offering non-volatile memory and analog weight storage.

Question 9: Which programming model supports neuromorphic systems?

Answer 9: Models like NEST and PyNN are used to simulate spiking networks.

Question 10: In which applications is neuromorphic computing ideal?

Answer 10: Robotics, sensory data processing, edge AI, and adaptive control systems.