Fine-Tuning adapts a general pretrained model using material such as a company’s customer-service records or specialized domain data. It can establish a distinctive tone or a consistent task format. Using it primarily to inject current knowledge is often inefficient because changing information would require repeated retraining; RAG is usually better suited to that need. Fine-tuning is more appropriate for stabilizing brand voice or output conventions, such as a fixed JSON response structure.
A strategy for optimizing content so that brands and their content can be cited in the single answers generated by AI search systems or voice assistants.
Search that uses large language models to understand context and synthesize web results into natural-language answers rather than relying solely on keyword matching.
Some websites are seeing sharp increases in site: operator queries in Search Console performance reports. Explore possible causes, measurement effects and diagnostic responses.
