How Enterprises Can Reduce AI Dependencies While Preserving Performance and Flexibility

AI-Era Data Protection Against Ransomware Attacks

Reducing Retrieval Cost and Complexity Without Compromising AI Quality

Why an equipment maker is funding a shared research center for competing chipmakers, and the ROI it expects.

How VAST Data enables consistent security, policy, and audit across data at rest, in transit, and in use

The HyperFRAME Research “Oracle’s Data-Centric AI Security Strategy: Because You Can’t Build an AI Foundation on Quicksand” Research Brief analyzes how shifting security directly to the data layer through Oracle’s Autonomous AI Database neutralizes machine-speed AI threats, eliminates architectural fragmentation, and provides a cost-effective roadmap to operational resilience. As AI drastically accelerates the speed and scale of cyber threats, traditional reactive security models are becoming obsolete. AI agents now identify and exploit system vulnerabilities at speeds that bypass human-led response workflows, creating a fundamental asymmetry in modern cybersecurity.

The HyperFRAME Research “The Next Generation of Data Lakehouses” Research Brief examines how enterprises can bridge the gap between production AI and fragmented data architectures by evolving the traditional lakehouse into a unified, operational intelligence platform. As enterprises shift AI from initial pilots to full production, data has emerged as the ultimate differentiator for success. This leaves IT leaders facing a core strategic dilemma: should they move their data to the AI, or deploy the AI directly to where their data lives?