Machine Learning vs. Artificial Intelligence: Understanding the Distinction

Terms like Machine Learning (ML) and Artificial Intelligence (AI) have become ubiquitous, often used interchangeably. However, they are distinct concepts that play crucial roles in the realm of technology and data-driven decision-making. In this article, we will delve into the differences between ML and AI, and explore the cutting-edge advancements of Jaxon in LLM machine learning.

AI is a broad and all-encompassing field of computer science that aims to create intelligent systems that can simulate human-like behavior, reasoning, and problem-solving. It encompasses various subfields, and one of the most prominent ones is ML.

ML is a subset of AI that focuses on designing algorithms and statistical models that enable computers to learn from data without being explicitly programmed for each task. Instead of following a predefined set of rules, ML systems can adapt and improve their performance over time by learning from the data they process.

AI is the broader concept that encompasses the development of intelligent systems, while ML is the specific technique within AI that enables machines to learn from experience and improve their performance on a given task.