While core updates typically result in big

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swings in rankings, Google typically provides very little details or guidance. This lack of transparency is done in part to prevent people from gaming the system. But in reality, these updates are also complex, made up of multiple parts, and likely complicated by the use of machine learning in the core algorithm. In short, even Google may not be able to explain or account for all the moving parts.


The future belongs to the machines… In October 2015, Google released RankBrain, a machine learning algorithm that has likely been running since at least that spring. This represented a shift in philosophy within Goo dominican republic whatsapp number data gle, away from over-reliance on human-vetted rules/heuristics. A lot has happened since then, and Google has at least three core deep learning components in play: RankBrain, DeepRank, and RankEmbed. In the spring of 2023, Google launched Search Generated Experience (SGE), built on Bard (recently renamed Gemini).




SGE uses a large language model (LLM) to attempt to answer natural language queries by combining information from multiple sites. Here’s a recent example: Here’s an example of SGE using an LLM to answer a natural language query by combining information from multiple sites. This begs the question: did SGE drive the unprecedented ranking volatility of summer 2023 (which has barely abated even in early 2024)? The short answer is “no.” Since SGE was only available to a limited number of logged-in users, and MozCast uses non-personalized search results, there’s no reason to believe SGE had a significant impact on our measurements.