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A Large Language Model is an autoregressive Transformer neural network with billions of parameters trained on vast corpora of text to iteratively predict the probability distribution of the next token given preceding context tokens.
“The world’s most sophisticated predictive autocomplete: having read all public literature, it understands human knowledge and context well enough to continue ideas coherently.”
// Autoregressive token generation loop
while (!isStopToken(token)) {
const logits = model.forward(contextTokens);
token = sample(logits);
contextTokens.push(token);
}Assuming LLMs possess feelings, sentience, or internal consciousness rather than high-dimensional statistical pattern matching.