Minimalist diagram showing BlockRank's approach to search ranking - traditional SEO signals filter candidate pages in the first layer, then neural network evaluates semantic relevance in the second layer

BlockRank and the Future of Ranking: Why Traditional SEO Still Matters

Google's new BlockRank research (covered in Search Engine Journal) shows how large language models can rank web pages by reading a query alongside multiple documents and determining which one best answers what the user's looking for. DeepMind calls this In-Context Ranking (ICR), and it represents a real shift toward evaluating pages based on meaning, not …

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