1. Introduction to AI
What is AI?
AI, or artificial intelligence, refers to the capability of machines, especially computer systems, to perform tasks that typically require human intelligence. To put it simply, AI systems can analyze data, make decisions, and solve problems in a way similar to the human brain.
Main subsets of AI
Now that you’ve understood “what is AI?”, you should know that it is not a technology. In fact, AI is a set of technologies that help machines learn, adapt, and interact more effectively with their environment. Below are the main subsets of AI.
- Machine learning vs AI: Machine learning (ML) is a branch of AI that enables computers to learn from data and improve their performance over time without being explicitly programmed to do so. With the ability to identify patterns and relationships within large datasets, machine learning algorithms can make predictions and decisions based on historical data analysis.
- Deep learning vs AI: Deep learning is not only a subset of AI but also an advanced subset of machine learning. At the heart of deep learning is neural networks, which are designed to resemble the structure of the human brain to analyze complex data. These networks consist of multiple layers of interconnected nodes (or neurons) that process information hierarchically, automatically learning features from large, often unstructured datasets. This layered structure enables deep learning algorithms to identify intricate patterns and relationships, making them particularly effective for applications like image recognition, speech processing, and natural language understanding.
- Natural language processing (NLP): Natural language processing (NLP) enables computers to understand and generate human language, both text and speech. By integrating machine learning, linguistics, and deep learning, NLP algorithms can interpret language to identify meaning, sentiment, and context. This technology powers a wide range of applications, from spam detection to advanced language models like ChatGPT, supporting tasks such as translation, speech recognition, and sentiment analysis.
- Computer vision: Computer vision is a subset of AI focused on enabling machines to interpret and understand visual information from digital images and videos. By using deep learning and convolutional neural networks, computers can break down images into pixels, label patterns, and detect objects. In other words, computers can “learn” to differentiate between objects in a similar way to human vision.
- Robotics: Robotics is the field focused on designing, manufacturing, and programming machines - robots - that can autonomously perform complex tasks. Robotics often incorporates AI, enabling robots to recognize objects, understand environments, and assist in areas like manufacturing, healthcare, and retail. Advanced AI-powered robots can even interpret emotions and interact with people.
