Learning in Machines and Brains

Learning in machines and brains is the process of improving performance by adjusting responses based on experience. In humans, it involves forming new connections in the brain through practice and understanding. In machines, it involves algorithms that analyze data to recognize patterns and make better decisions over time. While biological learning is complex and influenced by emotions and context, machine learning relies on mathematical models to adapt from data. Both systems aim to become more accurate or efficient with practice, enabling tasks like speech recognition, decision-making, or problem-solving without being explicitly programmed for every situation.