All news with #vertex ai tag

Google Named Leader in IDC Hyperscaler Marketplaces 2025

🚀 Google is recognized as a Leader in the 2025 IDC MarketScape for Worldwide Hyperscaler Marketplaces. The assessment highlights Google Cloud Marketplace for its integrated portfolio of SaaS, AI agents, foundational models, datasets, and services validated for enterprise readiness. The platform emphasizes AI innovation with a dedicated AI agent category, deep integration with Vertex AI and deployment via Gemini Enterprise. It also offers partner validation, enterprise governance tools, AI-driven discovery, flexible private offer buying, and global transaction support.

Apigee Adds Managed MCP Support for Secure APIs and Policy

🔒 Google’s Apigee now supports MCP with fully managed, remote servers, enabling organizations to expose existing APIs as agent tools without code changes or running MCP infrastructure. By creating an MCP proxy with your OpenAPI spec and a /mcp basepath, Apigee handles transcoding, protocol handling, and automatic registration in API hub. You can apply Apigee’s built-in security, identity, quota, and analytics controls to govern and monitor agent interactions. The capability is currently available in preview for a limited set of customers.

Google Patches Zero-Click Gemini Enterprise Vulnerability

🔒 Google has patched a zero-click vulnerability in Gemini Enterprise and Vertex AI Search that could have allowed attackers to exfiltrate corporate data via hidden instructions embedded in shared Workspace content. Discovered by Noma Security in June 2025 and dubbed "GeminiJack," the flaw exploited Retrieval-Augmented Generation (RAG) retrieval to execute indirect prompt injection without any user interaction. Google updated how the systems interact, separated Vertex AI Search from Gemini Enterprise, and changed retrieval and indexing workflows to mitigate the issue.

Nutanix NC2 Now Generally Available on Google Cloud

🚀 Nutanix Cloud Clusters (NC2) is now generally available on Google Cloud, enabling organizations to run their Nutanix hybrid cloud directly on Google Compute Engine bare metal without refactoring workloads. NC2 supports the Z3 and C4 machine families with high-density NVMe local SSDs, integrates Nutanix Flow virtual networking, and maintains unified management via Prism Central. The solution connects to Google data and AI services like BigQuery and Vertex AI, supports license portability, and will be purchasable through Google Cloud Marketplace.

MedGemma DICOM and FHIR Integration for Clinical Workflows

🩺 Google Health AI Developer Foundations has added DICOMweb support to MedGemma, releasing a public Docker container, container source code, and API specifications so teams can deploy DICOM-aware services that accept medical images as DICOMweb links. The update pairs with pre-built Vertex Model Garden resources for GCP users and leverages existing MedSigLIP containers that already understood DICOM. The post also demonstrates a FHIR navigation agent that uses the model’s awareness of FHIR to retrieve patient context without ingesting full records.

Replit and Google Cloud Expand Vibe Coding for Enterprise

🚀 Replit and Google Cloud have expanded a strategic, multi‑year partnership to bring vibe coding capabilities to enterprise developers and teams. Replit will continue to run on Google Cloud infrastructure—leveraging Cloud Run, Google Kubernetes Engine, BigQuery, and Vertex AI—and now supports Google models including Gemini 3, 2.5 Flash Lite, 2.5 Flash, and Imagen 4 to power coding and multimodal workflows. The agreement also includes joint go‑to‑market and co‑sell initiatives to accelerate adoption across enterprise customers.

PubMed Data in BigQuery to Accelerate Medical Research

🔬 Google Cloud has made PubMed content available as a BigQuery public dataset with integrated vector search via Vertex AI, enabling semantic search across more than 35 million biomedical articles. Both BigQuery and Vertex AI Vector Search are FedRAMP High authorized, allowing organizations to run embedding models and VECTOR_SEARCH queries inside BigQuery. Early adopters like The Princess Máxima Center report literature reviews reduced from hours to minutes, and example SQL plus a demo repo are provided to help teams get started.

Building a Production-Ready AI Security Foundation

🔒 This guide presents a practical defense-in-depth approach to move generative AI projects from prototype to production by protecting the application, data, and infrastructure layers. It includes hands-on labs demonstrating how to deploy Model Armor for real-time prompt and response inspection, implement Sensitive Data Protection pipelines to detect and de-identify PII, and harden compute and storage with private VPCs, Secure Boot, and service perimeter controls. Reusable templates, automated jobs, and integration blueprints help teams reduce prompt injection, data leakage, and exfiltration risk while aligning operational controls with compliance and privacy expectations.

Anthropic Claude Opus 4.5 Now Available on Vertex AI

🚀 Anthropic's Claude Opus 4.5 is now generally available on Vertex AI, delivering frontier performance for coding, agents, vision, and office automation at roughly one-third the cost of Opus 4.1. The model introduces advanced agentic tool use—programmatic tool calling (including direct Python execution) and dynamic tool search—plus expanded memory and a 1M-token context window to support long, multi-step tasks. On Vertex AI, Opus 4.5 is offered as a Model-as-a-Service on Google's high-performance infrastructure with prompt caching, efficient batch predictions, provisioned throughput, and enterprise-grade controls for deployment. Organizations can leverage the Agent Builder stack (ADK, A2A, and Agent Engine) and Google Cloud security controls, including Model Armor and Security Command Center protections, to accelerate production agents while managing cost and risk.

Google: Leader in 2025 Gartner Magic Quadrant for CDBMS

📈 Google announces it was named a Leader in the 2025 Gartner Magic Quadrant for Cloud Database Management Systems for the sixth consecutive year and positioned furthest in vision. The post presents the company's AI-native Data Cloud—a unified stack integrating BigQuery, Spanner, AlloyDB, Looker, and Dataplex—to support agentic AI. Google highlights embedded specialized agents, developer tooling (Data Agents API, ADK, Gemini CLI) and Agent Analytics in BigQuery to accelerate AI-driven applications while asserting cost and governance benefits on a single, open platform.

Vertex AI Studio adds Gemini tools for faster builds

🚀 Vertex AI Studio now centers developer workflows around Gemini and introduces agents-as-tools to streamline prompt engineering and app creation. The Studio adds three core agent commands — /Prompt, /Evaluate, and /Build — to refine prompts, assess outputs with custom autoraters, and generate working code. Team features include cross-account prompt sharing, version history, and notes. Onboarding is simplified with one-click API keys, an /Ask helper, express mode, and loginless model trials.

Agentic AI Framework for Life Sciences R&D on Google Cloud

🔬 Google Cloud outlines an agentic AI framework to accelerate life sciences R&D by orchestrating specialized, fine-tunable models into modular workflows. It describes four agents—MedGemma for deep literature and data synthesis, TxGemma for in-silico preclinical prediction, Gemini 2.5 Pro as the cognitive orchestrator, and AlphaFold-2 plus docking tools for molecular design. The architecture maps data flows, tooling, and cloud services (Vertex AI, HPC, search) to move from target discovery through iterative Design→Dock→Predict→Refine cycles toward lab-ready lead nomination while preserving version control and compliance.

Nano Banana Pro: Gemini 3 Pro Image for Enterprise Use

🎨 Google is unveiling Nano Banana Pro (Gemini 3 Pro Image), a high-fidelity image generation and editing model available today in Vertex AI and Google Workspace, with a rollout to Gemini Enterprise coming soon. The model supports multi-language text rendering and on-image translation, connects to Google Search for context-aware outputs, and accepts up to 14 reference images and 4K inputs for production-grade assets. Built-in SynthID watermarking and planned copyright indemnification address commercial use and responsible deployment.

Google Named Leader in Gartner MQ for AI Platforms

🚀 Google has been named a Leader in the inaugural 2025 Gartner Magic Quadrant for AI Application Development Platforms and ranked highest for Ability to Execute. The announcement highlights Vertex AI as a unified, governed platform that delivers model choice, customization, and production-grade agent capabilities across an enterprise. Key capabilities cited include the Vertex AI Model Garden and Gemini 3, Vertex AI Training, Agent Builder and Agent Engine for multi-agent systems, and operational controls for observability, security, and predictable cost.

BigLake Metastore Adds Iceberg REST Catalog Support

🔔 Google Cloud announced general availability of BigLake metastore support for the Iceberg REST Catalog, offering a serverless, standards-based runtime metastore that enables interoperability across Iceberg-compatible engines (Spark, Trino) and BigQuery. The service provides credential vending, integrated governance via Dataplex Universal Catalog for lineage and data quality, and a UX console for creating and managing Iceberg catalogs. By removing the need to run custom metastore deployments, BigLake metastore aims to reduce operational overhead while preserving enterprise scale and security.

TimesFM Integration Brings Forecasting to BigQuery

🕒 Google is integrating the TimesFM time-series foundation model into BigQuery and AlloyDB, enabling zero-shot forecasting on customer data without retraining. AI.FORECAST and AI.EVALUATE are now Generally Available in BigQuery, while AI.DETECT_ANOMALIES is in public preview. TimesFM 2.5 offers improved accuracy and lower latency, supports dynamic context windows up to 15K, and can return historical data with forecasts. AlloyDB preview lets users call TimesFM endpoints hosted on Vertex AI so operational data can be forecasted in-place, preserving data residency and reducing export overhead.

Gemini 3 Brings Multimodal and Agentic AI to Enterprise

🤖 Google has made Gemini 3 available to enterprises and developers via Gemini Enterprise and Vertex AI, bringing advanced multimodal reasoning and agentic capabilities to production teams. The model can analyze text, images, video, audio, and code together, supports a 1M-token context window, and improves frontend generation, legacy code migration, and long-running tool orchestration. Early partners report faster diagnostics, richer UI prototypes, and more reliable automation across business workflows.

Google Gemini 3 Appears on AI Studio Ahead of Release

🤖 Google’s Gemini 3 has been spotted in AI Studio, suggesting an imminent rollout that could begin within hours or days. The AI Studio entry references how temperature influences reasoning — noting "For Gemini 3, best results at default 1.0. Lower values may impact reasoning" — and highlights controls such as context size and temperature. Earlier sightings on Vertex AI show a preview build named gemini-3-pro-preview-11-2025, while Google is also testing an image model codenamed GEMPIX2 (Nano Banana 2).

Google announces Dhivaru subsea cable and regional hubs

📡 Google announced Dhivaru, a new Trans-Indian Ocean subsea cable linking the Maldives, Christmas Island, and Oman, and will build two new connectivity hubs in the Maldives and Christmas Island. The investment builds on the Australia Connect initiative and aims to improve reach, reliability, and resilience across the Indian Ocean, supporting AI services such as Vertex AI. The hubs will provide cable switching, content caching, and colocation to reduce latency, improve availability, and support local ecosystems.

Production-Ready AI with Google Cloud Learning Path

🚀 Google Cloud has launched the Production-Ready AI Learning Path, a free curriculum designed to guide developers from prototype to production. Drawing on an internal playbook, the series pairs Gemini models with production-grade tools like Vertex AI, Google Kubernetes Engine, and Cloud Run. Modules cover LLM app development, open model deployment, agent building, security, RAG, evaluation, and fine-tuning. New modules will be added weekly through mid-December.