Tag: Recommendation Engine

In this post, we elucidate the simple yet powerful idea of combining user profiles and item attributes to generate personalized content recommendations using LLMs. As demonstrated throughout the post, these models hold immense potential in generating high-quality, context-aware input text, which leads to enhanced recommendations. To illustrate this, we guide you through the process of integrating a feature store (representing user profiles) with an LLM to generate these personalized recommendations.

This is a guest post by Sam Bean and Nic Roberts II at StockX. In their own words, “StockX is a Detroit startup company revolutionizing ecommerce with a unique Bid/Ask marketplace—our platform models the New York Stock Exchange and treats goods like sneakers and streetwear as high-value, tradable commodities. With a transparent market experience, StockX […]