Oracle and Google Cloud integrate Gemini Enterprise with Oracle AI Database to architect secure, natural language access to mission-critical data.
How Context Engineering Separates Agent Demos from Production Systems
Why Internet Performance Monitoring Is Essential for Modern Applications
As enterprises transition from prototypes to production agents, managing fragmented multi-cloud infrastructure becomes a significant tax on innovation and speed.
Fresh debt financing points to a company using multiple growth levers to expand capacity, enterprise reach, and AI-era relevance.
Fund backs Accenture, Deloitte, and smaller AI-native shops; response to Anthropic leading enterprise LLMs and AWS release of AgentCore in late 2025
Series F financing reflects investor confidence in VAST’s growing role in the data layer that connects AI infrastructure to enterprise outcomes
IBM’s approach assumes patchable software; the embedded layer NXP addresses devices shipped with 20-year lifecycles that can’t be easily patched, and that gap is now the real PQC story
TPU 8t and TPU 8i split training from serving as Google targets 2.8x training gains and 80% inference price-performance improvements over Ironwood; approach is Google’s answer to NVIDIA Vera Rubin NVL72 and AWS Trainium3/
Google Cloud shows that storage is no longer a passive capacity layer in AI environments, as throughput, metadata intelligence, and low-latency data delivery become central to training, inference, and agentic workloads.
