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Posted 14 Sep 2024

2 min read

They developed Memristor semiconductor devices using metal-organic films instead of silicon-based technology. 

  • This material enables the Memristor to mimic the way the biological brain processes information using networks of neurons and synapses.

What is Neuromorphic computing?

  • Neuromorphic computing, or neuromorphic engineering, mimics the human brain's structure and function. 
  • It involves designing hardware and software that simulate neural networks and synapses to process information.

How does neuromorphic computing work?

  • It mimics biological brains using hardware like spiking neural networks (SNNs).
  • SNNs consist of nodes (spiking neurons) connected by artificial synapses, which use analog circuitry to transfer signals. 
    • This approach encodes data through discrete analog signal changes rather than binary systems used in standard computers.

Benefits of neuromorphic computing

  • Adaptability: To new stimuli, excelling at solving novel problems in real-time.
  • Event-driven computation: Ensuring only active parts consume energy, resulting in efficient power usage.
  • High performance: As it integrates memory and processing in neurons, reducing latency.
  • Parallel processing: Of multiple tasks across different neurons for faster operation.
  • Challenges of neuromorphic computing: Lack of benchmarks and standards; Limited accessibility and software; Decreased accuracy, etc.

Processing of information by brain

  • Neurons are the fundamental units of the brain and nervous system.
  • As messengers, these neurons relay information between different areas of the brain and to other parts of the body.
  • When a neuron becomes active or “spikes,” it triggers the release of chemical and electrical signals.
  • These signals travel via a network of connection points called synapses, allowing neurons to communicate with each other.
  • Tags :
  • Neuromorphic
  • Neurons
  • Memristor
  • Neuromorphic Computing
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