True or False: An LLM cannot answer questions about today's news due to its knowledge cut-off, but can do so with RAG.

Master your understanding of Generative AI with our comprehensive test. Use flashcards, multiple choice questions, and get detailed insights. Prepare for your test confidently!

The correct response is true because a large language model (LLM) has a fixed knowledge cut-off date, meaning it is only trained on data available up to that point. It cannot access or incorporate any information that has emerged in the news after that date. Therefore, for inquiries regarding current events or news occurring after the cut-off, the LLM is unable to provide accurate responses.

However, when a retrieval-augmented generation (RAG) approach is employed, the model's capabilities are enhanced. RAG combines the strengths of a generative model with a retrieval mechanism that accesses external databases or information sources. This allows the LLM to pull in up-to-date information directly related to current events, enabling it to answer questions about today's news accurately. This utilization of real-time data through an external source is what makes it possible for the model to stay relevant and informed regarding more recent developments, thus validating the statement.

Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy