Probing models like Claude and GPT with curated requests reveals insights into their training processes and knowledge cutoffs. Techniques such as "Incompressible Knowledge Probes" help estimate model parameters and analyze dataset mixtures by measuring token breakdowns.

Using GPT or similar LLMs for information retrieval can be likened to Google's "I'm Feeling Lucky" feature, providing a single result without displaying the full range of search results. This method may lead to a lack of comprehensive understanding and context in the information obtained.