Private Post-Training and Inference with TEEs for Frontier Models (www.workshoplabs.ai)

Workshop Labs has partnered with Tinfoil to launch Silo, a groundbreaking multi-GPU private post-training and inference stack for frontier AI models. Designed to address the privacy crisis in AI, Silo ensures that customer data remains exclusively accessible to the user, meaning neither Workshop Labs nor cloud providers can view it. This is achieved through the use of hardware-protected trusted execution environments (TEEs), which securely encrypt and isolate data even while being processed. Silo also incorporates a user-specific key management system, enhancing security for data at rest. The significance of Silo lies in its potential to reshape privacy standards in AI by eliminating the risks associated with data visibility during training and inference processes—a critical concern as AI tools become more pervasive in handling sensitive information. With performance impacts below 10%, Silo delivers robust security without burdening users with the costs and complexities of local deployments. This innovation not only aligns with a growing demand for privacy in AI but also sets a precedent for verifiable, trusted computing environments in the AI landscape, a crucial step towards establishing credible AI practices amid increasing scrutiny on data privacy.