Google Enhances Search with New Generative AI

Google has been incorporating generative AI capabilities into its services and products, and now the company’s flagship product is receiving new generative AI features that are intended to “better learn and make sense of information on the web.”
Google’s generative AI-powered Search experience (SGE) was introduced in May, and the company claims that it has since made enhancements based on user feedback, such as adding more images and videos to search results to provide context.

 

“Today, we’re sharing a few more upgrades to SGE to help you better learn and make sense of information on the web: whether it’s deepening your understanding of complicated concepts, boosting your coding skills or tracking down details within a complex topic,” it said.

 

Improved comprehension of code knowledge

Coding is one of the highlights of generative AI’s capabilities, and Google is currently improving our grasp of how to write code. The business said that it would begin adding additional capabilities to SGE “to make it easier to understand and debug generated code.” The improvements will color-code sections of code in overviews with syntax highlighting, making it quicker and simpler to recognize components like keywords, comments, and strings and improving your ability to quickly digest the code.

 

Online learning is simple

Additionally, Google is starting a test at Search Labs called “SGE while browsing.” The function will be accessible through the Google app for Android and iOS, and it will soon be available through Chrome on desktop.

The goal of “SGE while browsing” is to make it simpler to locate what you’re searching for when exploring the internet and to encourage deeper engagement with long-form content from publishers and producers. For instance, you might be reading a study about a cosmic occurrence that makes references to a previously unknown historical occurrence. However, the document is too long to read. Users will be able to tap the new function to view an AI-generated list of an article’s main points.

 

 

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