Scientific search engines cautiously test AI capabilities


Various search engines for finding scientific publications are being equipped with AI functions. The companies promise to be especially careful, as AI-generated misinformation could do great harm, especially in science.

On August 1, Elsevier, a large Dutch scientific publisher, released Scopus AI to a select group of 15,000 beta users. This is a GPT-3.5-based AI search for the existing Scopus database. The final product launch is planned for early 2024.

The promise of what Scopus AI can do is great: The tool is expected to provide researchers with a concise and reliable overview of research topics, including academic references; reduce reading time and the risk of hallucinations; provide easy navigation to further links; and enable natural language queries.

A graphical representation will soon be introduced, allowing users to dive into the relationships between different papers.


Digital Science, the company behind the popular Dimensions database search, is following suit, announcing on August 1 a closed testing period for an AI assistant that uses its own General Science BERT language model as well as OpenAI’s GPT models.

“When a user interacts with Dimensions AI Assistant, it scans 33 million articles from the Dimensions database, retrieves and then semantically ranks the top results using semantic embeddings,” explains head of innovation Martin Schmidt.

Summaries of the top four results are then processed by an OpenAI API to generate abstract summaries. Dimension’s General Science BERT model then provides the answers from the ten most relevant publications.

Video: Digital Science

Clarivate and its Web of Science product have similar plans. Its assistant will be based on a large language model from AI21 Labs, possibly a derivative of Jurassic-1. The idea is to give scientists quick access to detailed and contextual information and answers, as well as personalized recommendations, Clarivate said in a press release.


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