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?

- Accelerated Vector Search
- Mastering Audio AI
- The Definitive Guide to Building RAG Apps with LlamaIndex
- Embedding 101
- Getting Started with Zilliz Cloud
- 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
What is the role of distance metrics in image search?
Distance metrics play a vital role in image search by providing a way to measure how similar or different two images are
How do optimizers like Adam and RMSprop work?
Optimizers like Adam and RMSprop work by adjusting the weights of a neural network during training to minimize the loss
What is the difference between GPT and other LLMs?
GPT (Generative Pre-trained Transformer) focuses on generating text by predicting the next token in a sequence, making i