🤯 Did You Know (click to read)
Google incorporated BERT into search in 2019 to better interpret natural language queries.
BERT captures bidirectional context to understand the semantic intent of search queries. By encoding queries and documents into contextual embeddings, it allows search engines to match user questions with the most relevant passages, rather than relying solely on keyword overlap. This improves accuracy for natural language queries, including long-form and conversational inputs.
💥 Impact (click to read)
Semantic search enables users to find more accurate and relevant information quickly. Businesses, educators, and content platforms benefit from increased engagement and improved search precision.
For users, search results feel more intuitive and aligned with intent. The irony is that BERT achieves understanding statistically rather than cognitively.
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