AI Inference
AI Inference is the process of running a trained model on new input to generate output. It is the runtime execution phase, as opposed to training, where the model learns patterns from data.
Definition
During inference, the model applies everything it learned during training to new inputs. When you ask ChatGPT a question or trigger an AI search engine to answer a query, that is inference. Inference takes the pre-trained weights and generates output by predicting tokens sequentially.
Inference is what most users interact with. It is where LLMs generate answers, where retrieval-augmented generation retrieves your sources, and where your brand's content gets cited or ignored. Inference performance depends on the model's training, the prompts provided, and the retrieval quality.
Why it matters for AI visibility
Your brand's AI visibility is determined entirely at inference time. Once a model is deployed, your content's ranking depends on retrieval, reranking, and citation probability during inference. Understanding inference helps you grasp why real-time content updates and current information matter more than historical brand equity.
Related terms
Large Language Model (LLM)
Large Language Models are neural networks trained on massive text datasets to predict and generate human language. They form the foundation of modern AI search and answer engines.
AIRetrieval-Augmented Generation (RAG)
RAG is the technique of retrieving relevant documents at answer time, then using them to ground an LLM's response. It enables AI search engines to cite sources while generating answers.
AIPrompt Engineering
Prompt Engineering is the practice of crafting input text to reliably produce desired outputs from LLMs. It includes techniques for clarifying instructions, providing examples, and structuring queries.
GEOAI Search
AI Search refers to search and discovery systems powered by large language models that generate synthesized answers from multiple sources rather than rank-ordering links in a traditional search results page.