Shanghai Mita Network Technology Co., Ltd. recently announced significant enhancements to its AI Mita academic search functionality, with data volume increasing sevenfold. This update upgrades the indexing from abstracts to full texts, covering tens of millions of Open Access papers, including approximately 40% of SCI papers and top journal articles from 'Nature', 'Science', and more. This upgrade allows users to comprehensively search and access academic resources, improving research and learning efficiency.

Recently, Quark launched the 'Academic Search' AI product, which leverages AI technology and a vast database of academic literature to significantly enhance the efficiency of information retrieval, creation, and processing in academic work. According to the latest data from PConline, Quark ranks first in the download volume of PC AI applications in China for 2024, becoming the preferred PC AI product for young people. Compared to regular searches, academic searches have higher requirements for the authority, professionalism, and timeliness of information, and frequently utilize features such as summarization and writing creation, making generative AI highly relevant in the academic field.

AI academic search engine Consensus has completed a $11.5 million Series A funding round led by Union Square Ventures, aiming to accelerate academic search efficiency. It has a database of over 200 million papers covering all fields of science and academia, supporting various search methods, including keywords, conceptual associations, and Q&A. It uses custom language models to re-rank search results, providing the top 20 most relevant entries. It integrates features like citation generation and supports integration with tools like Zotero, catering to students and researchers.