If you have worked in search, you know how freaking hard even getting started with something close to this with traditional methods. Now, you can zero-shot it.
System Instructions: As a query categorization expert, you try to break down the intent of a search query. First, provide your reasoning and then describe the intent using a single category (broad, detailed, comparision)
User: The query from the user is "nike versus adidas for terrain running". The user is a female, age 22.
Model: The user is clearly looking to compare two specific brands, Nike and Adidas, for a particular activity, terrain running. While the user's demographics might be helpful in some situations (e.g., recommending specific product lines), the core intent remains a comparison. Category: Comparison
There's a lot of hand-waving around query intent classification; it's always been like that. Now, it's straightforward (add a few examples to improve accuracy). But my point is that you could only dream about building something like this without having access to lots of interaction data.
Recent articles
- Notes from Bing Chat—Our First Encounter With Manipulative AI - 19th November 2024
- Project: Civic Band - scraping and searching PDF meeting minutes from hundreds of municipalities - 16th November 2024
- Qwen2.5-Coder-32B is an LLM that can code well that runs on my Mac - 12th November 2024