llms

Computing & AI

AI & Language Models

• Tokens and EmbeddingsLLMs do not normally read text one character or one word at a time. A tokenizer converts text into integer token IDs representing chunks such as whole short words, word pieces, punctuation, or bytelevel patterns.
• Transformer AttentionAttention lets each token build a new representation by selectively combining information from other tokens in the context.
• What an LLM Actually PredictsAn autoregressive large language model is trained around an almost embarrassingly simple objective: given previous tokens, assign probabilities to the next token.
• Why Local vs Cloud AI Models DifferRunning an AI model locally versus through a cloud service changes where the weights and computation live, which in turn changes privacy, latency, hardware limits, cost structure, and model choice.