Generative AI
Invitation Code: RFP-23-02
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The advent of new large language models (LLMs) and other generative AI models has captured widespread interest and enthusiasm and has opened numerous opportunities across various domains, including education, healthcare, art and entertainment, human-technology interaction, and potentially addressing future challenges in human’s affairs. This great potential also may pose some risk that calls for carefully designed guidelines to ensure responsible use. The objective of this RFP is to invite proposals for research projects focused on diverse aspects of generative AI. Specific areas of research include by not limited to the following:

  • Training and fine-tuning and deployment of Large Language models as well as other generative AI models such as diffusion models.
  • Large-scale (stream) data processing with WASM
  • Responsible AI principles and consideration in design and adaptation of the large generative models. This may include addressing issues such as bias and fairness, attribution, robustness against adversarial attacks, reliability and trustworthiness, and the problem of hallucination.
  • Development of innovative new technologies and applications powered by generative AI, spanning areas such software development and design, security, education, future of work and collaboration, healthcare and more.

We seek innovative and impactful research proposals that will contribute to the responsible growth and utilization of generative AI technologies while maximizing their benefits and minimizing risks.


Proposal Submission:

After a preliminary review, we may ask you to revise and resubmit your proposal.

RFPs may be withdrawn as research proposals are funded, or interest in the specific topic is satisfied.

Researchers should plan to submit their proposals as soon as possible.

General Requirements for Consideration, Proposal Details, FAQs

You can find the information by scrolling down to the bottom of the webpage: Research Gifts. If your questions are not answered in the FAQs, please contact research@cisco.com.

Constraints and other information

IPR will stay with the university. Cisco expects customary scholarly dissemination of results and hopes that promising results would be made available to the community without limiting licenses, royalties, or other encumbrances.