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All news with #vertex ai tag

Thu, October 2, 2025

Accelerate AI with Agents: EMEA Developer Series and Labs

🚀 Google Cloud is hosting a regional event series across EMEA to help developers and tech practitioners learn to build and scale AI agents. The program combines immersive, hands-on labs and expert-led workshops covering technologies such as Cloud Run, Vertex AI, Gemini, and the Agent Development Kit (ADK). Participants receive step-by-step guidance and practical exercises designed to accelerate agent deployments and operational readiness within organizations.

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Mon, September 29, 2025

Anthropic's Claude Sonnet 4.5 Now Available on Vertex AI

🚀 Anthropic’s Claude Sonnet 4.5 is now generally available on Vertex AI, delivering advanced long-horizon autonomy for agents across coding, finance, research, and cybersecurity. The model can operate independently for hours, orchestrating tools and coordinating multiple agents to complete complex, multi-step tasks. Vertex AI provides orchestration, provisioning, security controls, and developer tooling, and includes Claude Code upgrades like a VS Code extension and an improved terminal interface.

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Wed, September 24, 2025

Enabling Data Scientists to Become Agentic Architects

🧭 Google outlines an AI-native stack to transform data scientists into agentic architects, unifying development, real-time data access, and production-grade agent deployment. Enhancements to Colab Enterprise notebooks add native SQL cells, editable visualizations, and an interactive Data Science Agent that can orchestrate BigQuery ML, DataFrames, and Spark workflows. The Lightning Engine is now generally available to accelerate Spark, while previews for stateful BigQuery continuous queries and autonomous embedding generation bring real-time streaming and vector search into analytics. A 'Build-Deploy-Connect' toolkit, including the Agent Development Kit, MCP Toolbox, and Gemini CLI extensions, helps move notebook prototypes into secure, scalable agent fleets.

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Wed, September 24, 2025

INDOT Used Google AI to Save 360 Hours and Meet Deadline

🚀 Indiana Department of Transportation built a week-long pilot on Google Cloud to meet a 30-day executive order, using a Retrieval-Augmented Generation workflow that combined rapid ETL, Vertex AI Search indexing, and Gemini. The system scraped and parsed decades of internal policies and manuals, produced draft reports across nine divisions with 98% fidelity, and saved an estimated 360 hours of manual effort, enabling INDOT to submit on time.

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Wed, September 24, 2025

JS Bank modernizes with Google stack and ChromeOS rollout

🚀 JS Bank migrated its distributed IT estate to a unified Google ecosystem—deploying 1,500 Chromebooks and Chromeboxes while adopting Google Workspace and Chrome Enterprise Premium. The change delivered nearly 90% endpoint standardization, cut device management time by 40%, and halved daily support tickets. Built-in ChromeOS protections simplified security and reduced reliance on multiple third-party antivirus and anti-malware tools.

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Tue, September 23, 2025

Deutsche Bank launches DB Lumina for AI research platform

🤖 DB Lumina is Deutsche Bank Research’s AI-powered assistant, built on Google Cloud and integrating multimodal Gemini models, RAG retrieval, and vector search. It provides a conversational chat interface, reusable prompt templates, and document-grounded answers with inline citations and enterprise guardrails for compliance. Early deployment to roughly 5,000 analysts has yielded measurable time savings, deeper analysis, and improved editorial accuracy.

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Mon, September 22, 2025

Protect AI Development Using Falcon Cloud Security

🔒 Falcon Cloud Security provides end-to-end protection for AI development pipelines by embedding AI detection into CI/CD workflows, scanning container images, and surfacing AI-related packages and CVEs in real time. It extends visibility to cloud model services — including AWS SageMaker and Bedrock, Azure AI, and Google Vertex AI — revealing model provenance, dependencies, and API usage. Runtime inventory ties build-time detections to live containers so teams can prioritize fixes, govern models, and maintain delivery velocity without compromising security.

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Thu, September 18, 2025

Seattle Children’s Uses AI to Accelerate Pediatric Care

🤖 Seattle Children’s partnered with Google Cloud to build Pathway Assistant, a multimodal AI chatbot that turns thousands of pediatric clinical pathway PDFs into conversational, searchable guidance. Using Vertex AI and Gemini, the assistant extracts JSON metadata, parses diagrams and flowcharts, and returns cited answers in seconds. The tool logs clinician feedback to BigQuery and stores source documents in Cloud Storage, enabling continuous improvement of documentation and metadata.

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Thu, September 18, 2025

Mr. Cooper and Google Cloud Build Multi-Agent AI Team

🤖 Mr. Cooper partnered with Google Cloud to develop CIERA, a modular agentic AI framework that assembles specialized agents to support mortgage servicing representatives and customers. The design assigns distinct roles — orchestration, task execution, data retrieval, memory, and evaluation — while keeping humans in the loop for verification and personalization. Built on Vertex AI, CIERA aims to reduce research time, lower average handling time, and preserve trust and compliance in regulated workflows.

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Thu, September 18, 2025

Google Cloud's Differentiated AI Stack Fuels Startups

🚀 Google Cloud highlights how its differentiated AI tech stack is accelerating startup innovation worldwide, with nine of the top ten AI labs, most AI unicorns, and more than 60% of generative AI startups using its platform. Startups are leveraging Vertex AI, TPUs, multimodal models like Veo 3 and Gemini, plus services such as AI Studio and GKE to build agents, generative media, medical tools, and developer platforms. Programs like the Google for Startups Cloud Program provide credits, mentorship, and engineering support to help founders scale.

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Wed, September 17, 2025

BigQuery scalability and reliability upgrades for Gen AI

🚀 Google Cloud announced BigQuery performance and usability enhancements to accelerate generative AI inference. Improvements include >100x throughput for first-party text generation and >30x for embeddings, plus support for Vertex AI Provisioned Throughput and dynamic token batching to pack many rows per request. New reliability features—partial-failure mode, adaptive traffic control, and robust retries—prevent individual row failures from failing whole queries and simplify large-scale LLM workflows.

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Wed, September 17, 2025

California Modernizes Public Services with Google Cloud

🚀 California is partnering with Google Cloud to modernize state and local services by applying AI, security, and infrastructure solutions. Agencies such as Covered California use Document AI, Assured Workloads, and AI-driven security to speed eligibility decisions and protect sensitive data. Universities including UCR and Caltech are using Vertex AI and AI-optimized HPC for research acceleration. Workspace, Gemini, and Agentspace are cited as productivity and information-management enablers.

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Tue, September 16, 2025

Gemini and Open-Source Text Embeddings Now in BigQuery ML

🚀 Google expanded BigQuery ML to generate embeddings from Gemini and over 13,000 open-source text-embedding models via Hugging Face, all callable with simple SQL. The post summarizes model tiers to help teams trade off quality, cost, and scalability, and introduces Gemini's Tokens Per Minute (TPM) quota for throughput control. It shows a practical workflow to deploy OSS models to Vertex AI endpoints, run ML.GENERATE_EMBEDDING for batch jobs, and undeploy to minimize idle costs, plus a Colab tutorial and cost/scale guidance.

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Tue, September 16, 2025

Data Science Agent Adds BigQuery ML, DataFrames, and Spark

🧭 Google Cloud has expanded the Data Science Agent in Colab Enterprise notebooks to support BigQuery ML, BigQuery DataFrames and Spark, enabling large-scale data transformation, model training, and inference directly on BigQuery or via Serverless for Apache Spark. The agent can now auto-retrieve BigQuery table metadata and lets you add tables via an @ mention from your current project to provide prompt context. To invoke frameworks, include keywords such as BigQuery ML, BigFrames, or PySpark; sample prompts are provided to guide forecasting, supervised learning, and dimensionality reduction workflows. Notable limitations: generated PySpark targets Spark 4.0 and @ mentions only search the current project; BigQuery improvements are available now in BigQuery notebooks and coming soon to Vertex AI.

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Tue, September 16, 2025

New Practical Guide to Data Science with Google Cloud

📘 Google Cloud has published a new ebook, A Practical Guide to Data Science with Google Cloud, aimed at practitioners adopting an AI-first approach across BigQuery, Vertex AI, and Serverless for Apache Spark. The guide emphasizes unified, streamlined workflows enabled by a central notebook experience that blends SQL, Python, and Spark and includes assistive features in Colab Enterprise to generate multi-step plans and code. It explains how a unified data foundation lets teams manage structured and unstructured data together and use familiar SQL to process documents and images. The ebook also offers real-world use cases with linked notebooks so practitioners can run the examples and accelerate delivery.

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Tue, September 16, 2025

Google Cloud and SAP: Unified Data, AI Agents, and HANA

🚀 Google Cloud and SAP announced tighter integration to unify enterprise data and accelerate intelligent automation. SAP Business Data Cloud now connects to BigQuery via Datasphere, enabling bidirectional replication and AI-ready analytics. Procurement is simplified on the Google Cloud Marketplace with SAP BTP. New agent tooling—Agentspace, the Agent Development Kit, A2A and MCP standards—and expanded M4 memory-optimized VMs certified for SAP HANA aim to speed deployments, improve data consistency, and enable autonomous process automation.

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Wed, September 10, 2025

Conversational Commerce Agent on Vertex AI Released

🛒 Google Cloud announced general availability of the Conversational Commerce agent on Vertex AI, a shopping-focused conversational assistant designed to guide customers from intent to purchase. The agent uses Gemini to interpret complex queries, supports context retention across sessions and devices, and offers administrative controls to boost, bury, or restrict products. Albertsons Cos. reports increased basket size in early use. Onboarding is presented as quick with minimal development effort via the Vertex AI console.

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Tue, September 9, 2025

Google Cloud Releases Official Rust SDK for Developers

🚀 Google Cloud has released an official Rust SDK that provides idiomatic, supported access to more than 140 Google Cloud APIs. The SDK includes built-in authentication (ADC, OAuth2, API Keys, service accounts, and upcoming Workload Identity Federation), documentation, and code samples to streamline development. It targets high-performance backends, secure data processing, and real-time analytics, and the project is available on crates.io and GitHub for feedback and contributions.

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Tue, September 9, 2025

Partner-built AI Security Innovations on Google Cloud

🔒 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.

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Thu, September 4, 2025

StreamSight: AI-Powered Music Royalty Forecasting Tool

🔍 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.

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