Artificial Intelligence refers to the simulation of human intelligence in machines to enable them to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, and decision-making.
AI systems can learn from data and experiences, improving their performance over time.
They can analyze information, draw conclusions, and make decisions based on available data.
AI is used to solve complex problems and optimize processes.
AI is applied in various domains, including natural language processing, computer vision, robotics, virtual assistants, autonomous vehicles, healthcare, finance, and more.
Machine learning is a subset of AI that focuses on the development of algorithms and models that allow computers to improve their performance on a task through experience (data).
Machine learning is widely used in recommendation systems (e.g., Netflix recommendations), fraud detection, image and speech recognition, autonomous vehicles, healthcare diagnostics, and many more areas.
In summary, AI encompasses the broader concept of creating machines that can mimic human intelligence, while machine learning is a specific subset of AI that focuses on enabling machines to learn from data. Machine learning is a critical tool within the field of artificial intelligence, and both play vital roles in various technological advancements and applications .