Google Search Generative Experience Gets Major Update to Improve Answers

Google Search Generative Experience (SGE) has been updated with a speed boost and quality updates. SGE now generates answers twice as fast

has released its first set of quality updates to the new Search Generative Experience (SGE) that began to rollout a few weeks ago. The most noticeable update is that it is much faster, in fact, twice as fast, in responding with an AI-generated snapshot/answer.

In addition to the speed boost, Google has also made some improvements to the quality of the SGE answers. For example, the answers are now more likely to be relevant to the user's query, and they are less likely to contain irrelevant or duplicate information.

Google is still working on improving the SGE, and it is likely that more updates will be released in the future. However, the initial set of quality updates is a positive sign that Google is committed to making the SGE a valuable tool for users.

Here are some of the specific improvements that Google has made to the SGE

  • Answers are now more relevant to the user's query. Google has improved the way that it analyzes user queries to determine which answers are most likely to be relevant. This has resulted in a significant decrease in the number of irrelevant answers that users are seeing.
  • Answers are less likely to contain irrelevant or duplicate information. Google has improved the way that it filters out irrelevant and duplicate information from the answers that it generates. This has resulted in a cleaner and more concise experience for users.
  • Answers are now more likely to be complete. Google has improved the way that it generates answers to long and complex queries. This has resulted in a decrease in the number of answers that are missing important information.

What is Search Generative Experience?

Google announced SGE in May.  The service is powered by large language models (LLMs) such as Pathways Language Model 2 (PaLM2) and Multitask Unified Model (MUM), which can generate natural language text from multiple sources of information. SGE can answer complex and multi-step questions by synthesizing a “snapshot” of relevant information from different webpages and presenting it at the top of the search results. Users can also ask follow-up questions to get more specific or detailed information.

For example, a user who wants to buy a laptop can ask SGE about the basic features to look for, and get a summary of different articles that contain the query. The user can then ask for laptop recommendations under a certain budget, and get a list of options from Google's Shopping Graph, which includes sponsored products.