What AI is and the differences between AI, ML, and DL.
Artificial Intelligence (AI) is a broad and multifaceted field of computer science dedicated to creating systems capable of performing tasks that typically require human intelligence. This includes capabilities like reasoning, problem-solving, learning, perception, and language understanding. AI is not a single technology but an umbrella term for a collection of approaches and algorithms. A common way to conceptualize AI is through the idea of an 'agent' that perceives its environment and takes actions to maximize its chance of successfully achieving its goals. Within this broad field lies Machine Learning (ML), a specific and powerful subset of AI. Instead of being explicitly programmed with rules to perform a task, ML algorithms are designed to learn patterns and make predictions directly from data. The core idea is that by analyzing a large number of examples, the machine can infer the underlying rules on its own. Further specializing, we find Deep Learning (DL), a subfield of ML. DL is based on Artificial Neural Networks (ANNs) with many layers (hence 'deep'). These deep architectures allow the model to learn a hierarchy of features, from simple patterns in the initial layers to complex, abstract concepts in the deeper layers. This hierarchical feature learning is what has enabled breakthroughs in areas like image recognition and natural language processing. So, the relationship is hierarchical: DL is a type of ML, which is a method for achieving AI.