AI refers to the simulation of human intelligence by machines, enabling them to perform tasks like reasoning, problem-solving, and decision-making.
Scope: Broad, includes all types of AI systems.
ML is a subset of AI focused on enabling machines to learn from data and improve over time without being explicitly programmed.
Generative AI creates new content, such as images, text, music, or code, using patterns in existing data. It leverages models like GANs or Transformers (e.g., GPT models).
Key Feature: Emphasis on 'creation' rather than just classification or prediction.
Agentic AI refers to AI systems capable of autonomous action, making decisions, planning, and executing tasks independently in dynamic environments.
Scope: Mostly theoretical or experimental, often discussed in advanced AI contexts.
Key Difference: Ability to act independently to achieve objectives.
Understanding these distinctions is crucial for navigating the evolving landscape of AI technologies and applications.