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Generative AI as a personal agent for knowledge management processes

Unleash the power of Artificial Intelligence and generative models in the pharmaceutical industry together with Boehringer Ingelheim by developing personalized AI agents that support health workers in knowledge management, research & content creation.

#KnowledgeManagement #PersonalAIagent #GenerativeAI

  • ‚úÖ Challenge completed
  • ūüŹĀ Winner
    Congratulations to Curiousity AI (1st place) & Arkangel AI (2nd place) for winning the challenge!
  • ūüŹÜ  Rewards
    Funded Co-Creation + versatile collaboration models for implementation
  • ūüďÉ Venture clienting

    BI is searching for a long-term partner to implement the solution

Opportunity Areas

Generative AI as a personal agent

Information workers in the pharmaceutical industry often struggle with information overload, making it challenging to extract key insights from an ever-growing pool of research papers, clinical trial results, regulatory guidelines, and market reports.

With the new possibilities provided by generative AI, various work processes can be simplified and made more efficient. We are looking for a text processing model that can revolutionize the way knowledge is summarized and facilitate efficient decision-making processes.

Your task

The goal of this Challenge is to utilize a large language model (LLM) that can analyze and process a wide range of sources, leveraging either an existing (open source) LLM or building a new one. The objective is to generate high-quality pharmaceutical summaries and articles that effectively capture essential information in a coherent and accurate manner.

Goals and outcome

The goal is to find innovative solutions that help to design such an interaction and interface between humans and machines. For this purpose, a concept with proof-of-concept is to be submitted in the first phase, as well as the concept and outline for further implementation.

The participation is aimed at start-ups, companies and researchers who have chances for partnerships up to (research) collaborations and hiring.

To approach the problem step by step, participants can refer to the instructions in the tab ‚ÄúOpportunity Areas‚ÄĚ for inspiration.

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