LLM

An artificial intelligence model trained on large volumes of text that generates natural language statistically. The best known are GPT (OpenAI), Claude (Anthropic), and Gemini (Google). They don’t “understand” in the human sense: they predict the next word based on learned patterns. That makes them useful for text, semantic classification, and conversation, but they can hallucinate facts.

When should I use LLM at a company?

Tasks involving free-form text: summarization, extraction, semantic classification, translation, conversation, and assisted writing. The input must be unstructured text, and the output must be text or a semantic decision.

When is it NOT a good idea LLM?

Precise numerical predictions, decisions based on structured tabular data, or contexts where a hallucination can be costly without a validation layer in place.