What is machine learning?

Machine learning is indeed a subset of artificial intelligence that empowers systems to learn from data, identifying patterns, making predictions, and improving their performance based on experience without being explicitly programmed for every task. This capability allows computers to dynamically adapt and enhance their functionality over time as they are exposed to more data.

Machine learning systems use algorithms that can analyze large datasets, learn from them, and make decisions or predictions based on that learned information, often achieving higher accuracy and efficiency compared to traditional programming approaches which rely on predefined rules.

In contrast, traditional programming involves explicitly coding all the rules and logic for a system to follow, which does not allow for adaptive learning or improvement based on new information. Creating new algorithms, while related, does not encompass the full scope of what machine learning achieves. Similarly, while robotics can incorporate machine learning, it primarily focuses on the physical tasks and movements of robots rather than the data-driven learning aspect that defines machine learning.