All news with #vertex ai tag

🔒 Google Cloud and its partners announced a range of partner-built AI security solutions now available in the Google Cloud Marketplace. These integrations embed Gemini and Vertex AI into partner products — including CrowdStrike, Palo Alto Networks, Fortinet, and others — to protect models, data, applications, and agents. The collaborations emphasize automated detection, incident response, DLP, identity protection, and agent monitoring to reduce mean time to detect and respond, helping customers adopt AI securely.

🔍 StreamSight is an AI-driven application developed by BMG in partnership with Google Cloud to improve transparency, speed, and accuracy in digital royalty forecasting and anomaly detection. The solution leverages BigQuery ML models (including ARIMA_PLUS and BOOSTED_TREE), uses Vertex AI and Python for training, and surfaces results in Looker Studio dashboards. It flags missing sales periods, rights mismatches, and sudden streaming spikes to reduce manual review and help accelerate fairer payouts. Currently a proof of concept, StreamSight is positioned for broader DSP integrations and richer data inputs to extend its capabilities.

🔔 This month Google Cloud expanded its AI stack across models, tooling, and security. Highlights include Gemini 2.5 Flash with native image generation and SynthID watermarking on Vertex AI, new Veo video models, the Gemini CLI, and a global Anthropic Claude endpoint. Google also published 101 gen‑AI blueprints, developer guidance for choosing tools, and security advances for agents and AI workloads.

☁️ Google Public Sector has been awarded a $48 million DLA Enterprise Platform contract to migrate the Defense Logistics Agency to a DoD‑accredited commercial cloud. The multi‑phased program will move key infrastructure and data to a modern, AI‑ready Google Cloud foundation and enable BigQuery, Looker, and Vertex AI analytics. Emphasizing secure‑by‑design infrastructure and Mandiant threat intelligence, the effort aims to reduce costs, improve resiliency, and accelerate AI‑driven logistics and transportation management.

🚀 Gemini on Google Distributed Cloud (GDC) is now generally available for customers, bringing Google’s advanced Gemini models on‑premises with GA for air‑gapped deployments and a connected preview. The solution provides managed Gemini endpoints with zero‑touch updates, automatic load balancing and autoscaling, and integrates with Vertex AI and preview agents. It pairs Gemini 2.5 Flash and Pro with NVIDIA Hopper and Blackwell accelerators and includes audit logging, access controls, and support for Confidential Computing (Intel TDX and NVIDIA) to meet strict data residency, sovereignty, and compliance requirements.

🖼️ Google announced native image generation and editing in Gemini 2.5 Flash Image, now available in preview on Vertex AI. The model delivers state-of-the-art capabilities including multi-image fusion, character and style consistency, and conversational editing to refine visuals via natural-language loops. Built-in SynthID watermarking supports responsible, transparent use. Developers and partners report promising integrations and low-latency performance for real-time editing workflows.

⚙️ This guide from Google Cloud authors Eric Hanley and Brittany Rockwell explains how to tune vLLM deployments for xPU inference, covering accelerator selection, memory sizing, configuration, and benchmarking. It shows how to gather workload parameters, estimate HBM/VRAM needs (example: gemma-3-27b-it ≈57 GB), and run vLLM’s auto_tune to find optimal gpu_memory_utilization and throughput. The post compares GPU and TPU options and includes practical troubleshooting tips, cost analyses, and resources to reproduce benchmarks and HBM calculations.