Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Trusted Hardware for AI Workloads - Extending Confidential Computing to Enable AI Adoption

USENIX via YouTube

Overview

Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Explore the critical challenges and opportunities in securing AI workloads through trusted hardware in this 20-minute conference talk from USENIX Security '25. Examine how confidential computing and trusted execution environments are being extended from traditional CPUs to clusters of AI accelerators as companies rapidly adopt AI technologies. Learn about the key technical contributions needed from security experts, including efficient remote attestation and key management systems, secure interconnects, and robust device memory protection mechanisms. Discover how these advancements can provide stronger security guarantees while maintaining the performance and code compatibility essential for commercial AI adoption. Gain insights from industry experience in evaluating emerging technologies, offering a comprehensive perspective on both the commercial potential and technical feasibility of implementing trusted hardware solutions for large-scale AI deployments.

Syllabus

USENIX Security '25 (Enigma Track) - Trusted Hardware for AI Workloads: Extending Confidential...

Taught by

USENIX

Reviews

Start your review of Trusted Hardware for AI Workloads - Extending Confidential Computing to Enable AI Adoption

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.