What is the difference between artificial intelligence, machine learning, and deep learning?
Artificial Intelligence (AI) is a broad field of computer science that deals with the development of intelligent computer systems. AI systems aim to mimic human intelligence and perform tasks that would normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Machine Learning (ML) is a subset of AI that involves the creation of algorithms that allow computer systems to automatically learn and improve from experience, without being explicitly programmed. Machine learning algorithms use data to train models that can then make predictions or take actions based on new data inputs.

Deep Learning (DL) is a subfield of machine learning that involves the use of artificial neural networks, which are designed to mimic the structure and function of the human brain. Deep learning algorithms use multiple layers of interconnected nodes to learn and make decisions based on large amounts of data.

In summary, AI refers to the development of intelligent computer systems, machine learning involves the creation of algorithms that allow systems to learn from data, and deep learning involves the use of artificial neural networks for learning and decision-making.
That's a great breakdown! Is it possible to go ever deeper and mention a subfield of deep learning?
Of course! Deep learning has many subfields, such as natural language processing, computer vision, and reinforcement learning. Natural language processing involves the use of algorithms to understand and generate natural language, while computer vision involves the use of algorithms to recognize and classify objects in images and videos. Reinforcement learning is a type of machine learning algorithm that uses rewards and punishments to learn how to perform tasks.

Is there anything else you wish to know regarding deep learning and its subfields?