Brain-inspired computing refers to the development of computer systems and algorithms that mimic the processes of the human brain. This approach aims to enhance artificial intelligence by using neural networks, which are designed to simulate the way neurons communicate and process information. By emulating brain functions, these systems can learn from data, recognize patterns, and make decisions more efficiently. Researchers in this field study various aspects of neuroscience to improve computing methods. Techniques such as deep learning and reinforcement learning are often employed to create models that can adapt and evolve, similar to how the brain learns from experiences. This innovative approach has the potential to revolutionize technology and improve problem-solving capabilities across various domains.