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Articles from Product Experts and Googlers

LLMs vs. embeddings for Contextual Relevance Assessment

In many real-world applications, we encounter tasks that sit at the intersection of semantic understanding and contextual judgment. One such common scenario is determining if a set of keywords truly aligns with a brand, its products, and its messaging (like a tagline). This isn't just about whether the words are synonyms; it's about relevance in a specific context. Does "eco-friendly" align well with a fast-fashion brand's new line, even if the tagline mentions "sustainable materials"? Does "high-performance" fit a budget-friendly product?

From data to metadata: Unlocking insights with Gen AI in BigQuery

Metadata is essential for various data initiatives, from deploying NLP solutions and chat with your data applications to enabling semantic search and establishing a business glossary. However, the manual effort of documenting every data attribute within a platform can be time-consuming and error-prone. At Google Cloud Next, we announced BigQuery Data Insights and Automated Metadata Generation, two powerful capabilities that simplify this process using Gen AI.

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