Google Scholar has entered the ai revolution. Google Scholar PDF Reader Now Uses Generative ai Powered by Google ai Gemini tool to create interactive outlines of research articles and provide direct links to sources within the article. This is designed to make reading the relevant parts of the research paper more efficient, it says Anurag Acharya, co-founder of Google Scholar on November 18, 2004, twenty years ago last month.
In honor of Google Scholar's 20th anniversary, Acharya shares how teachers and their students can make the most of the new ai features available through the Chrome extension. Google Scholar PDF Reader.
Acharya, a former computer science professor at the University of California, Santa Barbara, grew up in India. As a student, he was frustrated by the lack of access to research materials available in India. When he arrived in the United States, he says he got off the plane a better researcher than in India.
“I had access to resources, but I didn't get smarter,” he says.
But even in the United States, access to much-needed academic material was often difficult to find for academics and researchers in various fields. Acharya and his Google Scholar co-founder Alex Versta realized this was slowing down research. They decided to take the lessons they had learned from developing Google search and apply them to the world of academic articles, research, and study. The goal was to make it more efficient for all researchers to take advantage of existing research, Acharya says. It has also helped make academic work more accessible to students, educators, and enthusiasts in general. But ai now allows the tool to go one step further.
<h2 id="utilizing-ai-for-deeper-research-3″>Using ai for deeper investigation
“Scholar, for a long time, has been about helping you find things,” Acharya says. “There are a lot of different ways we help people find things. Finding research is a key component, but reading, understanding and following up is another very important part of taking advantage of other people's research.”
The Google Scholar PDF reader, powered by artificial intelligence, is designed to help people navigate each individual document, Acharya says. It does this in several ways.
For example, anyone who has done research has come across a quote they want to examine. But when you read the article, this usually comes in the form of a reference in square brackets and you should look for it in the citations section of the article. Then you must copy and paste the name of the other document.
“You put it into some other search service and hopefully you can find some way to get to that document,” Acharya says. Google Scholar PDF turns that initial reference into a link and makes it easy to navigate to that second article.
Additionally, Google Scholar PDF uses ai to create an annotated table of contents for each article. Typically, a table of contents is just section headings, Acharya says, but this creates quick bulleted descriptions of what's in each section of the document. You can then click on these bullets to navigate directly to that part of the document.
“So you can skim through the parts you want and you can go into detail about the parts you want or decide, 'I know enough about this and I don't need it,'” Acharya says. He adds that the tool could help make a long paper less intimidating for a student researching this type of topic for the first time.
<h2 id="the-future-of-generative-ai-as-an-aid-to-research-3″>The future of generative ai as an aid to research
Acharya says that generative ai's ability to understand language so well is one of the features that makes these models so powerful.
“The fundamental ability to understand language will allow us to do many more things,” says Acharya. “The first thing is to find and read. The second is basically being able to understand an entire group.”
For Google Scholar, Acharya would like generative ai to be able to quickly summarize research related to any article a person is reading. This could identify research that seems to contradict that article, as well as new research that has appeared since its publication. Doing this is not possible at this time, but Acharya has built his career by asking complicated and difficult questions and, ultimately, discovering the answers.
Ultimately, Acharya is excited about the new era of generative ai. “It is a wonderful moment to be able to participate in these efforts. “There are so many things possible,” he says. “I think we've only scratched the surface, so I'm looking forward to what's to come.”
