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Undermind

Undermind

Undermind

Main Task


Undermind constitutes a scientifically-grounded application that uses state-of-the-art AI technology to perform academic research on behalf of its user.

It is devised to meticulously examine a myriad of academic papers, distilling from them the exact information requested, regardless of the inherent complexity.

Undermind surpasses traditional search engines by reconceptualizing search processes to imitate the careful, systematic human discovery process. This process prompts Undermind to scrutinize results in stages, utilizing language models for critical tasks such as the acknowledgment of essential information and adjusting the search strategy.

Undermind has been employed effectively to find pinpoint solutions for various complex problems in different fields such as Quantum Computing, Artificial Intelligence, Information Science and more.

Regardless of the topic, users can precisely describe what they need to Undermind as they would discuss with a colleague. The service prides itself on intelligent adaption.

It does not merely regurgitate search results as most engines do, but it adapts, based on what it learns from reading hundreds of papers. It is additionally programmed to recognize when it has found all relevant information.

Future plans involve incorporating full text discovery for even more complex discovery goals. Notably, Undermind sources its data from the Semantic Scholar database which includes over 200 million articles from diverse databases.

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Pros & Cons


  • Scientifically-grounded application
    Performs academic research
    Examines myriad of academic papers
    Reconceptualizes search processes
    Utilizes language models
    Adjusts search strategy
    Effective in various fields
    Intelligent adaption
    Recognizes relevant information
    Future full text discovery
    Sources from Semantic Scholar
    Trusted by renowned institutions
    Accurate results
    Comprehensive discovery
    Brainstorm with a copilot
    Solves real, complex problems
    Adaptive search methods
    Searches abstracts and metadata
    Redesigned search experience
    Sourced by two PhDs


  • Limited to Semantic Scholar database
    No full text search
    Searches take 2-3 minutes
    Might miss specific papers
    Search process in stages
    Potential information overload
    No multi-language support
    No collaborative research feature
    Unclear update schedule
    Complex search can confuse

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