VMware Private AI

Private AI is an AI architectural approach that aims to balance the business gains from AI with the practical privacy and compliance needs of the organization. VMware AI Labs has worked across VMware R&D and with our industry partners to create a platform for AI services that ensures privacy, control and choice while maintaining quick time-to-value.

Unlocking Tomorrow's Intelligence

AI Labs is dedicated to shaping a more intelligent future through its incubation projects and cutting-edge AI research, driving the evolution of AI within VMware and beyond.

Project Trinidad

Project Trinidad detects zero-day attacks in Modern Applications by applying Machine Learning to layer 7 East-West API traffic. Traffic is collected in kernel using eBPF. Our Machine Learning models infer normal application behavior from this traffic, and can detect anomalies that are symptomatic of threats and attacks.

Project Cypress

A new project will seamlessly integrate generative AI with VMware NSX, enhancing NDR through a user-friendly natural language interface for threat assessment. Our advanced AI/ML features will automate threat prioritization and offer actionable remediation guidance, streamlining root cause analysis and resolution. Look forward to elevate your security efforts with Project Cypress.

Confidential Computing

Confidential Computing offers guest applications end-to-end secure enclave support on the VMware vSphere platform. We designed generic enclave execution control and attestation/certifications APIs that make minimal assumptions on the underlying hardware capabilities. Looking toward the future, we are building a partner ecosystem to help accelerate the adoption of confidential computing while positioning VMware as a leader in multi-cloud security.

Research in AI

The VMware Research Group (VRG) works on trustworthy, private and resource efficient AI/ML and the underlying systems and algorithms that make AI possible. VRG creates unique differentiation for VMware’s products and advances the state of the field through impact on the research community.

Learn more about what’s new.

DoCoFL: Downlink Compression for Cross-Device Federated Learning

DoCoFL offers a comprehensive and novel downlink framework for cross-device Federated Learning that significantly reduces the downlink bandwidth requirements without degrading ML performance.

Advancing Research in the Memory Sub-System

Memory management is a complex and intricate area in operating systems. Explore our advances in memory sub-systems that impact the performance of existing and emerging workloads.

Research Publications

AI Labs Research brings university and industry researchers together to push the boundaries of technology. Explore our diverse set of recent publications to learn more about our work in AI and Systems.

Responsible AI

As AI/ML technologies see increasing adoption in important societal applications, it is critical to develop and deploy these techniques responsibly with a clear set of guiding ethical principles.

Unleashing the Power of AI with Ethical Integrity

At VMware, our adoption of ethical AI principles must align with both our EPIC2 values and our ESG goals to build trustworthy and safe AI systems, which respect privacy, security and content ownership policies, and behave in a fair and transparent manner.

Ready to Get Started?