Daily Dose of Data Science | Avi Chawla | Substack·37wHow Do LLMs Work?
Large Language Models work by predicting the next word in a sequence using conditional probability. They calculate probabilities for each possible next word given the previous context, then select the most likely candidate. To avoid repetitive outputs, LLMs use temperature sampling which adjusts the probability distribution - low temperature produces focused, predictable text while high temperature creates more random, creative outputs. The models learn high-dimensional probability distributions over word sequences, with trained weights serving as the parameters of these distributions.
