IARPA is seeking information on established characterizations of vulnerabilities and threats that could impact the safe use of large language models (LLMs) by intelligence analysts. This RFI is issued for planning purposes only, and it does not constitute a formal solicitation for proposals or suggest the procurement of any material, data sets, etc. The following sections of this announcement contain details on the specific technology areas of interest, along with instructions for the submission of responses.
LLMs have received much public attention recently due, among other things, to their human-like interaction with users. These capabilities promise to substantially transform and enhance work across sectors in the coming years. However, LLMs have been shown to exhibit erroneous and potentially harmful behavior, posing threats to the end-users.
This RFI aims to elicit frameworks to categorize and characterize vulnerabilities and threats associated with LLM technologies, specifically in the context of their potential use in intelligence analysis.
IARPA requests that submittals briefly and clearly describe the approach or capability, directly address any or all of the specific questions, and outline any known critical technical issues/obstacles. If appropriate, respondents may also choose to provide a non-proprietary rough order of magnitude (ROM) estimate regarding what such approaches might require in terms of funding and other resources for one or more years to support IARPA image simulation needs. This announcement contains all of the information required to submit a response. No additional forms, kits, or other materials are needed.
IARPA welcomes responses from all capable and qualified sources from within and outside of the U.S. Because IARPA is interested in an integrated approach, responses from teams with complementary areas of expertise are encouraged.
Responses to this RFI are due no later than 5 p.m., Eastern Time, on 21 August, 2023. All submissions must be electronically submitted to [email protected] as a PDF document. Inquiries to this RFI must be submitted to [email protected]. Do not send questions with proprietary content. No telephone inquiries will be accepted.
