Google It or Ask the Robot?

"Google it" has been the universal answer to every argument at the dinner table and half the questions in a group chat for years, but times are changing. As AI models continue to improve, even google results usually include an AI-generated summary of the request. The differences between a traditional web search and a detailed prompt might not be immediately obvious, but as any artist will tell you, there is a greater cost to creating something new than retrieving a thing that already exists.

A search engine is essentially a librarian with all of the books. You enter a query, and it retrieves a ranked list of documents from across the web, based on relevance, authority, and a hefty amount of SEO gaming. It's fast, cheap (computationally), and mostly just points you in the direction of where the answer might be. The real work of reading, filtering, and synthesizing is still up to the user. In contrast, a prompt to an AI model, doesn't retrieve anything in real time. It generates a response based on patterns learned during training, where massive amounts of text are compressed into numerical relationships. Each word is mapped into a high-dimensional vector space and the model uses matrix multiplications to predict what comes next, statistically, one token at a time.

Where a web search is like flipping through a file cabinet, prompting a large language model is like running a simulation every time you ask a question. It's like the difference between grabbing a few books from the shelf and publishing a brand new book. Search excels at surfacing authoritative sources and giving users control over context. AI models shine when the goal is drafting or synthesis, if the user doesn't mind a bit of probabilistic guessing.

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