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This is a small code lab to run SEV-SNP Confidential VMs on a local single-node k8s cluster.
This code lab assumes you have a SEV-SNP machine and a recent Linux distro with kernel 6.11+ (e.g. CentOS Stream 10, Debian Trixie, or Ubuntu 24.04.2).
The Rising Tide of Enterprise AI and the Imperative for Provable Privacy in LLM Inference Systems
Executive Summary
As enterprises rapidly adopt Large Language Models (LLMs) to transform their operations, they face a critical dilemma: unleashing AI's full potential requires processing sensitive data, yet current cloud-based solutions lack verifiable privacy guarantees. This document presents the case for provable privacy—a paradigm shift from trust-based to technically demonstrable data protection—as the essential bridge between AI innovation and enterprise security requirements.
1. The Enterprise AI Revolution
Artificial Intelligence, particularly Large Language Models, has evolved from experimental technology to strategic imperative. Organizations across sectors are embedding LLMs into their core operations—from code generation and data analysis to customer service and decision support. This transformation is backed by substantial investment, with most enterprises planning significant increases