In the rapidly evolving world of artificial intelligence (AI), one term has emerged with increasing importance: Language Model, especially large language models, then called Large Language Models. You’ve likely already used tools like chatGPT, deep learning models that generate coherent, human-like text. If so, you’ve already experienced the capabilities of large language models. In this article, we’ll delve deeper into what language models are, how they work, and explore some important examples from the scientific literature. Linguistic Models In short, a language model is software that can predict the probability of a sequence of words . Language models are trained on large

In the world of artificial intelligence, we often hear two terms: machine learning (ML) and deep learning (DL). Both are methods for implementing AI through the training of machine learning algorithms, which are then used to make predictions about the future and make decisions. These two subjects use different approaches and have different capabilities and characteristics. In this article, we’ll explore the differences between the two and better understand how they work. Machine Learning Machine learning is the discipline of designing algorithms capable of making predictions by learning patterns from past data. A machine learning algorithm differs from a “classic” computer science