J.D. Bean

Learn how Bee built a personal AI assistant where privacy is cryptographically guaranteed - not policy-promised. Bee processes user data exclusively within hardware-isolated EC2 Confidential VMs powered by AWS Nitro, where no one - including Amazon - can access unencrypted data.

You already run security and governance on AWS with IAM, CloudTrail, KMS, and VPC boundaries, and AI workloads on Amazon Bedrock inherit all of it. This chalk talk shows how: IAM scoping for model access, data perimeter policies, full prompt and response logging in CloudTrail, and KMS encryption at rest and in transit.

The AWS Nitro System revolutionized cloud computing by providing always-on confidential computing, ensuring AWS has zero operator access to customer data. While AWS offers various ways to assure this protection, today we are introducing Nitro Isolation Engine as an enhancement to the Nitro System.

Regulated industries face unique challenges in adopting AI while maintaining compliance. Explore four fundamental privacy-preserving primitives that unlock AWS AI capabilities: encryption with AWS KMS, confidential computing with AWS Nitro System, federated learning, and cryptographic computing.

At AWS, safeguarding the security and confidentiality of customers’ workloads is a top priority. AWS Artificial Intelligence (AI) infrastructure and services have built-in security and privacy features to give customers control over their data.

Join this hands-on workshop to learn how to isolate highly sensitive data from your users, applications, and third-party libraries on your Amazon EC2 instances using AWS Nitro Enclaves. Explore Nitro Enclaves, discuss common use cases, and run a sample application inside an enclave.

Join this chalk talk to learn how to architect a solution where multiple parties can securely share data, AI/ML models, and compute while preserving the privacy and confidentiality of both data and code.