Last February, Bing introduced LLM-powered chat answers, setting the stage for a significant transformation in search technology. Now, Microsoft is taking it a step further with the introduction of Bing’s generative search. This new feature, currently being tested with a small percentage of user queries, promises to offer a search experience that aims to surpass what Google tries to do with AI Overview.
What is Bing generative search?
Bing generative search combines generative AI and large language models (LLMs) to create dynamic, tailored responses to user queries. Unlike traditional search results that just list links, generative search provides detailed, context-rich information directly within the search results. Here is how it works:
When you enter a search query, Bing uses LLMs to understand the intent behind your search. It considers the context and specifics of your query. Bing’s AI reviews millions of information sources across the web, matching the most relevant content to your query.
The AI crafts a detailed response, summarizing key points, historical context, examples, and more. This response is designed to be clear and informative.
The AI-generated response appears alongside traditional search results. This way, you get a comprehensive answer quickly, while still having the option to explore more through the links provided.
Why Bing generative search is different?
Bing’s generative search offers detailed answers directly within the search results. Instead of making users click multiple links to gather information, Bing provides comprehensive responses on the results page. This approach saves time and effort, giving you the information you need in one clear summary.
Bing’s generative search also improves the user experience. The AI-generated responses are easy to read, making it simple to understand even complex topics. This straightforward presentation helps users quickly grasp the information without getting overwhelmed.
Additionally, Bing generative search supports web publishers by displaying traditional search results alongside AI-generated content prominently. This ensures that publishers continue to get traffic to their websites, maintaining the web’s ecosystem of information sharing.
Finally, the AI-generated responses in Bing’s generative search include many clickable links. These references validate the information and encourage users to explore the original sources further. This approach promotes deeper learning and allows users to dive into more detailed content if they want to.
The future
Microsoft is committed to refining Bing’s generative search. The feature is being rolled out gradually, allowing for user feedback to drive ongoing improvements. Early data suggests that this approach maintains website clicks, supporting a healthy web ecosystem.
Microsoft aims to do what Google hasn’t yet achieved: revolutionize the search experience by integrating traditional search results with the power of AI and LLMs. This is just the beginning, and there’s more to come as Bing continues to innovate and enhance the way you search.
Can they succeed? Time will tell, but I believe there will be no winner in this race. The search page, which users have relied on for years, has become overly complicated. Additionally, it seems unethical for search engines to use data from websites in this manner. Even though early data shows it doesn’t affect the number of clicks, most users search for simple answers. If search engines “steal” this information from websites and use it directly, it could negatively impact the industry.
