AI Under the Hood
Knowing the difference between a general AI tool and one trained on specific sources can mean the difference between getting an accurate answer and becoming quickly frustrated with outcomes that either don’t answer the question thoroughly or answer the question in a confused mixture of fact and fiction. While not always clear, the data that lies behind the GenAI tool is just as important to consider as the user interface or the cost. Without trustworthy or relevant underlying information, the resulting AI-generated output will be less helpful or less trusted and result in inefficiencies as lawyers and staff work to fill the gaps in the GenAI’s response. Considering these factors, Kristopher Turner’s article identifies how and why a retrieval augmented generation (RAG) can give focused and highly specific answers related to one area that someone needs to quickly understand.
