Artificial intelligence (AI) and machine learning (ML) are two terms that are often used interchangeably. However, there is an important difference between these two concepts.
Artificial intelligence refers to the ability of computers to simulate human-like thinking and decision making. AI systems can access and process complex data and make decisions normally reserved for a human mind. AI encompasses a wide range of technologies including speech recognition, image recognition, robotics, and autonomous systems.
In contrast, machine learning is a subcategory of AI that refers to the ability of computers to learn from data without being explicitly programmed. ML systems use algorithms to identify patterns in data and build models that allow them to make predictions or decisions. The goal of ML is to automatically learn how to make decisions by gathering past experience.
An example of the difference between AI and ML is speech recognition software. AI technology allows the software to recognize and interpret human-like speech patterns. However, the ML model that the software uses can only learn how to better understand and recognize human speech through repeated training on large data sets.
Another example of the difference between AI and ML is a self-driving car. The car's AI technology allows it to make decisions and detect obstacles. However, the car's ML model allows it to learn how to better detect obstacles and respond to the environment through repeated training on big data.
An important aspect of ML is that it can be both supervised and unsupervised. Supervised learning refers to ML systems that learn from examples provided by a human expert. Unsupervised learning refers to ML systems that recognize patterns in data without a human expert having programmed the model in advance.
Overall, the difference between AI and ML is important to understand as it helps to better define the capabilities and applications of these technologies. While AI encompasses a broad range of technologies that simulate human-like reasoning and decision making, ML refers to a specific method of learning from data. Both technologies have the potential to change the way we work and live in the future.