This article explores the origins and inner workings of language models, a foundational technology behind AI systems like ChatGPT. It explains how these models, based on probability calculations, predict and generate text, drawing examples from everyday experiences like predictive text and smart speakers.
The arrival of AI systems called large language models , like OpenAI’s ChatGPT chatbot, has been heralded as the start of a new technological era and they may indeed have significant impacts on how we live and work in future.
Language models are designed to estimate how likely it would be to see a particular sequence of words. This is where probabilities come in. Neural networks rely on large numbers of numerical values to help understand these connections between words. These parameters must be set correctly in order for the model to work well.
A side effect of this change is that it allowed transformers to be trained on vastly more documents than was possible for previous approaches, producing larger language models. Training on problems like these has made transformers more flexible and powerful than previous language models.
AI Language Models Chatgpt Predictive Text Probability
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