On the safe use of diffusion-based foundation models

As generative foundation models are used in an increasing number of realms, concerns about privacy have accompanied their spread. Canada CIFAR AI Chair Mi Jung Park will address safety concerns related to diffusion models by using computationally-efficient and utility-preserving techniques. The project focuses on two important areas: not-safe-for-work (NSFW) content generation, and data privacy/memorization– reducing risks of models memorizing private information, like social security numbers, from training datasets. By developing techniques for removing problematic datapoints, they will aid in developing safer, privacy-preserving foundation models.