Artificial Intelligence (AI) is the broader concept of machines being able to perform tasks that typically require human intelligence, such as reasoning, problem-solving, and decision-making. Machine Learning (ML) is a subset of AI that focuses on training systems to learn patterns from data without being explicitly programmed. AI encompasses a wide range of techniques and applications, including rule-based systems, robotics, and expert systems. For example, a chess-playing program that follows predefined strategies can be considered AI even if it does not use machine learning. ML, in contrast, uses algorithms to learn from data. For example, a machine learning model can be trained to classify emails as spam or not spam based on historical data. While all ML is AI, not all AI involves ML; AI can also include techniques beyond learning from data.
What is the difference between AI and Machine Learning?
- Mastering Audio AI
- AI & Machine Learning
- Natural Language Processing (NLP) Basics
- Advanced Techniques in Vector Database Management
- Master Video AI
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
Why might DeepResearch be taking significantly longer than expected to complete a query?
DeepResearch might take longer than expected to complete a query due to a combination of computational complexity, infra
What is schema matching in knowledge graphs?
Schema matching in knowledge graphs is the process of identifying and aligning the structure and semantics of different
How do distributed databases handle time synchronization?
Distributed databases handle time synchronization primarily through the use of timestamps and synchronization protocols