Listen: Large Language Model
A language model at sufficient scale — billions of parameters, trained on web-scale text — to exhibit emergent capabilities like reasoning, instruction following, and open-ended generation. Gemini, GPT, Claude, and Llama are all LLMs.
Transcript
At their core, large language models are AI systems trained on a massive scale. By processing billions of parameters and trillions of words from books, code, and the open web, these models develop entirely new capabilities. While smaller models are good at sorting and retrieving information, true large language models can actually reason, synthesize, and generate original content. They power the AI assistants we use every day, like Google Gemini, OpenAI’s GPT, and Anthropic’s Claude.
Almost all of these models work by predicting the very next word in a sequence. Because of their scale, they can write coherent long-form essays, translate languages, write code, and follow complex, nuanced instructions. But this scale also makes their internal behavior much harder to predict or audit.
For anyone working in search engine optimization, these models change everything. They have become the new interface between a user's question and the internet's answers. Even when these AI models pull in fresh web results to ground their answers, their underlying training still shapes which sources they trust and how they represent brands. Moving forward, the real challenge of SEO isn't just understanding search algorithms anymore—it is understanding how these large language models think and behave.