The Inner Workings of Large Language Models Revealed

Large language models use embeddings of words and parallel computations to predict the next word in a sentence.

Multi-layer perceptrons and attention heads enable large language models to process and interpret the input.

Components specialized in grammar and linguistic constructions play a crucial role in language models.

Large language models rely on queries, keys, and values to communicate and exchange information.

Training large language models involves running machine learning algorithms on large amounts of text.

How do large language models predict the next word in a sentence?

—Large language models use embeddings of words and computations performed by multi-layer perceptrons and attention heads to predict the next word.

What role do components specialized in grammar play in language models?

—Components specialized in grammar help language models understand and interpret the input, allowing them to make accurate predictions.

How do large language models exchange information?

—Large language models use queries, keys, and values to communicate and exchange information between different components.

How are large language models trained?

—Training large language models involves running machine learning algorithms on large amounts of text to find the optimal set of numbers for performing the prediction task.

What enables large language models to make accurate predictions?

—Large language models combine knowledge of grammar, linguistic constructions, and factual information to make accurate predictions.

00:06When entering a question into a chatbot, the sentence is broken down into words or tokens and each word is mapped to embeddings.

00:16Large language models perform computations in parallel for each word, predicting the next word at each processing step.

00:24The computations in large language models start with initial predictions and gradually refine them based on the input.

00:34Large language models may have uncertainties in their predictions at the beginning processing steps.

00:56Large language models use components specialized in grammar and linguistic constructions to improve predictions.

01:22Language models take into account the context and knowledge of the input to make accurate predictions.

02:00Components like attention heads allow language models to ask for and provide information to other components.

04:58Large language models process the input word by word, combining information from all previous words to make predictions.