AI and ML defined
1. AI and ML defined
People commonly use the terms artificial intelligence, AI, and machine learning, ML interchangeably. The confusion is understandable because artificial intelligence and machine learning are closely related. However, these trending technologies differ in several ways, including scope and application. Before we advance, let's define each of the terms. Artificial intelligence is a broad field which refers to the use of technologies to build machines and computers that can mimic cognitive functions associated with human intelligence. These functions include, being able to see, understand, and respond to spoken or written language, analyze data, make recommendations and more. Although artificial intelligence is often thought of as a system in itself, it's a set of technologies implemented in a system to let it reason, learn, and act to solve a complex problem. Machine learning is a subset of AI that lets a machine learn from data without being explicitly programmed. It relies on various models to analyze large amounts of data, learn from the insights, and then make predictions and informed decisions. Machine learning algorithms improve performance over time as they are trained or exposed to more data. Machine learning models at the output, or what the program learns from running an algorithm on training data. When more data is used, the model improves. One helpful way to remember the difference between the two is to imagine them as umbrella categories. Artificial intelligence is the overarching term that covers a variety of specific approaches and algorithms. Machine learning sits beneath that umbrella, but so do other major sub fields such as deep learning, robotics, expert systems, and natural language processing. Another area of AI you may be hearing a lot about is generative AI. This is a type of artificial intelligence that can produce new content, including text, images, audio, and synthetic data. Google applies generative AI to products like Google Workspace to help users easily automate different types of tasks, like generating summaries of long documents. Google also provides development tool kits, such as generative AI APIs to developers to help them create customized products and services. Generative AI can be used in a variety of applications, such as conversational bots, content generation, document synthesis, and product discovery.2. Let's practice!
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