Neuromorphic computing is a rapidly evolving field that seeks to emulate the way the human brain processes information. The idea is to create computer systems that can learn and adapt like humans, rather than simply following pre-programmed instructions. This approach has the potential to revolutionize artificial intelligence (AI) and machine learning, enabling computers to perform tasks that are currently beyond their capabilities.
One of the key challenges in developing neuromorphic computing systems is creating hardware that can simulate the complex interactions between neurons in the brain. Traditional computer architectures are not well-suited to this task, as they rely on a rigid set of instructions that are executed in a linear fashion.