What is the term for a type of artificial intelligence that mimics the functioning of the human brain?

The term for a type of artificial intelligence that mimics the functioning of the human brain is a neural network. Neural networks are designed to simulate the way neurons in the human brain work, enabling them to recognize patterns, learn from data, and make decisions based on the information they process. This architecture consists of interconnected nodes (or neurons) that process inputs and can adjust their connections (or weights) based on learning algorithms.

Neural networks excel in tasks such as image and speech recognition, making them widely used in fields like computer vision and natural language processing. These systems learn from large datasets, adjusting their internal parameters to improve their accuracy over time, mimicking the learning process found in biological brains.

Other concepts mentioned, such as genetic algorithms, expert systems, and fuzzy logic, serve different purposes in the realm of artificial intelligence and do not directly replicate the brain's architecture or functioning. Genetic algorithms use evolutionary concepts to optimize solutions, expert systems apply rule-based reasoning to mimic human expertise in specific fields, and fuzzy logic deals with reasoning that is approximate rather than fixed and exact. While these methods are valuable in their own rights, they do not reflect the neural structure and learning processes inherent in neural networks.