Intel announced advancements across silicon, software and services, showcasing how it brings together technologies and the ecosystem to unlock business value for customers and in the future. Trust Assurance for the Hybrid Workforce: Businesses operate in and depend on the cloud to support remote workforces that require multiple devices, uninterrupted access and collaboration tools. Technology solutions need to secure data not only in memory and in transit, but also in use – protecting valuable assets and minimizing attack surfaces. Project Amber provides organizations with remote verification of the trustworthiness of a compute asset in cloud, edge and on-premises environments. This service operates independent of the infrastructure provider hosting the confidential compute workloads. Confidential computing, the protection of data in use by performing computation in a hardware-based trusted execution environment (TEE), is a growing market. Intel® Software Guard Extensions (Intel® SGX) available on the Intel® Xeon® Scalable platform is one of the main technologies powering confidential computing today, enabling cloud-use cases that are beneficial for organizations that handle sensitive data on a regular basis. The foundational basis of trust in a confidential computing environment is established via a process called attestation. The verification of this trustworthiness is a critical requirement for customers to protect their data and intellectual property as they move sensitive workloads to the cloud. To raise trust assurance and drive forward the promise of confidential computing for the broader industry, Intel announced Project Amber as the first step in creating a new multi-cloud, multi-TEE service for third-party attestation: Designed to be cloud-agnostic, this service will support confidential computing workloads in the public cloud, within private/hybrid cloud and at the edge. Interposing a third party to provide attestation helps provide objectivity and independence to enhance confidential computing assurance to users. In its first version, Project Amber intends to support confidential compute workloads deployed as bare metal containers, virtual machines (VMs) and containers running in virtual machines using Intel TEEs. The initial release will support Intel TEEs, with plans to extend coverage to platforms, devices and other TEEs in the future. Intel is also working with independent software vendors (ISVs) to enable trust services that include Project Amber. New software tools, such as published APIs that enable ISVs to incorporate Project Amber to augment software and services, will complement Intel's platforms and technologies, and bring more value to customers and partners. Intel plans to launch a customer pilot of Project Amber in the second half of 2022, followed by general availability in the first half of 2023. Paving the Way for Secure and Responsible AI Artificial intelligence (AI) propels technology even further, enabling insights and automation to handle greater scale. With this proliferation of sensitive information, the threat landscape grows, as do the surrounding security concerns. That's why Intel is committed to developing artificial intelligence that is secure and responsible. Highlighting the criticality of AI outcomes being used as a force for good, Intel emphasized the key question technologists should ask before they decide to continue pursuing development: Does the technology contribute to improving our society? Maintaining data integrity, accuracy and privacy is at the heart of Intel's industry-leading research efforts. Intel demonstrated how it is accelerating AI deployments in ways that are responsible and secure to help customers and partners solve complex problems: BeeKeepererAI uses Intel SGX hardware-based security capabilities and Microft Azure's confidential l computing infrastructure to provide a zero-trust platform. It enables an AI algorithm to compute against multiple real-world clinical datasets without compromising the privacy of the data or the intellectual property of the algorithm model. This is accelerating healthcare AI development and deployment innovation by more
than 30% to 40% when compared to the current method.