Shannon Egan, Deep Science Ventures
As companies race to adopt AI in new use cases, hardware vendors and cloud providers are developing the protocols to secure AI workloads with limited input from the broader security community. This talk surveys key challenges of extending Confidential Computing and Trusted Execution Environments from CPUs to clusters of AI accelerators, highlighting technical contributions needed from security experts: efficient remote attestation and key management, secure interconnects, and device memory protection. These advancements would enable stronger security guarantees while maintaining performance and code compatibility—crucial requirements for commercial adoption. We draw from our experience evaluating market opportunities for emerging technologies to offer a unique perspective on both the commercial potential and technical feasibility of trusted hardware for large-scale AI.
Shannon Egan is a Founder in Residence at Deep Science Ventures and an R&D Creator with the UK’s Advanced Research + Invention Agency (ARIA). Her work combines market scoping with fundamental research on devices for next-generation computing and hardware security.
