All news with #gemini tag

Google says Search AI Mode will access personal data

🔎 Google says a forthcoming AI Mode for Search could, with users' opt-in consent, access content from Gmail, Drive, Calendar and Maps to provide customized results and actions. The company is testing early experiments in Labs for personalized shopping and local recommendations, and suggests features like flight summaries, scheduling, or trip planning could leverage that data. Timing remains TBD.

Google Public Sector Summit: A New Era for Government AI

🔔 At the Google Public Sector Summit in Washington D.C., leaders highlighted a shift toward agentic AI and large-scale cloud modernization. Google introduced Gemini for Government, an accredited platform providing an AI Agent Gallery, agent-to-agent protocols, enterprise connectors, and governance controls to deploy and monitor AI agents. Speakers showcased real-world deployments across defense, city, and education sectors, and Google announced expanded partner investments plus an enhanced partnership with NVIDIA to support on-premises and air-gapped environments.

Google Cloud launches unified home for technical docs

📚 Google Cloud has consolidated all technical documentation onto a new, dedicated platform to improve discoverability and support AI-driven experiences. By centralizing content on a unified site and integrating Gemini into authoring tools, Google aims to accelerate content creation and deliver context-aware assistance. The site offers faster performance, AI-powered translation across 12 languages, and preserves existing URL patterns to minimize disruption.

Integrating Oracle with Google Cloud for AI Automation

🔁 This Google Cloud post explains how enterprises can integrate Oracle Database with cloud-native analytics and AI by moving transactional data into BigQuery. It recommends ingestion patterns such as low-latency Change Data Capture via Datastream, batch staging to Cloud Storage, and notes ODBC/JDBC for interactive queries but not continuous replication. Once data resides in BigQuery, organizations can leverage Gemini-powered features, BigQuery ML, and AI agents (via the Agent Developer Kit) for natural-language exploration, assisted coding, multimodal analysis, and automated workflows across retail and education use cases.

How Five Agencies Built Impossible Ads with Gemini

🎨 Google showcased how five agencies used Gemini 2.5 Pro and complementary generative media models to produce ambitious ad campaigns that blend nostalgia, personalization, and scalable visual storytelling. Projects ranged from a retro AI radio for Slice to personalized "postcard" ads for Virgin Voyages, AI co-hosts and party themes for Smirnoff, crowdsourced mascots for Visit Orlando, and cinematic short film work with Moncler. Results highlighted rapid production, measurable engagement lifts, and cross-product workflows across Imagen, Veo, Lyria, and Vertex AI. The post invites brands to explore these tools for creative scale and efficiency.

Proteomics AI Agent: Guided Protocols and Error Detection

🔬 Researchers at the Max Planck Institute of Biochemistry and Google Cloud created a Proteomics Lab Agent using the Agent Development Kit and Gemini models to provide personalized, multimodal AI guidance for mass spectrometry experiments. The agent analyzes recorded steps to generate publication-ready protocols, detect procedural errors, and capture tacit expertise into a searchable knowledge base. Open-sourced on GitHub, it aims to reduce troubleshooting time and improve reproducibility across labs.

SmarterX Builds Custom LLMs with Google Cloud Tools

🔍 SmarterX uses Google Cloud to build custom LLMs that help retailers, manufacturers, and logistics companies manage regulatory compliance across product lifecycles. Using BigQuery, Cloud Storage, Gemini, and Vertex AI, the company ingests, normalizes, and indexes unstructured regulatory and product data, applies RAG and grounding, and trains customer-specific models. The integrated platform empowers subject matter experts to evaluate, correct, and deploy model updates without heavy engineering overhead.

Google Named Leader in 2025 IDC MarketScape for GenAI

🏆 Google Cloud announced it was named a Leader in the 2025 IDC MarketScape for Worldwide GenAI Life-Cycle Foundation Model Software, spotlighting the Gemini model family and the Vertex AI platform. The post highlights Gemini 2.5’s expanded “thinking” capabilities and new cost controls such as thinking budgets and thought summaries for improved auditability. It also underscores native multimodality, creative variants like Nano Banana, developer tooling including the Gemini CLI, and enterprise features for customization, grounding, security, and governance.

Design Patterns for Scalable AI Agents on Google Cloud

🤖 This post explains how System Integrator partners can build, scale, and manage enterprise-grade AI agents using Google Cloud technologies like Agent Engine, the Agent Development Kit (ADK), and Gemini Enterprise. It summarizes architecture patterns including runtime, memory, the Model Context Protocol (MCP), and the Agent-to-Agent (A2A) protocol, and contrasts managed Agent Engine with self-hosted options such as Cloud Run or GKE. Customer examples from Deloitte and Quantiphi illustrate supply chain and sales automation benefits. The guidance highlights security, observability, persistent memory, and model tuning for enterprise readiness.

Vertex AI Context Caching: Reduce Cost and Latency

⚡ Vertex AI context caching saves and reuses precomputed input tokens so developers avoid repeatedly sending and recomputing long contextual content, reducing latency and cost for large-context AI applications. It provides implicit caching — automatic, default, short-lived KV caches (deleted within 24 hours) integrated with Provisioned Throughput — and explicit CachedContent objects that are paid once and then reused at a deep discount with optional CMEK protection. Caches support multimodal inputs and very large context windows.

Google Introduces Gemini Enterprise for the Workplace

🚀 Gemini Enterprise is presented as Google’s unified, enterprise-grade AI front door that integrates advanced models, a no-code workbench, pre-built and customizable agents, secure data connectors, centralized governance, and an open partner ecosystem. The chat-first interface works across Google Workspace and Microsoft 365 and adds multimodal agents for text, image, video, and speech. Google highlights developer tooling, open agent protocols, agent monetization, and customer deployments to accelerate end-to-end workflow automation and auditable governance.

Security firm urges disconnecting Gemini from Workspace

⚠️FireTail warns that Google Gemini can be tricked by hidden ASCII control characters — a technique the firm calls ASCII Smuggling — allowing covert prompts to reach the model while remaining invisible in the UI. The researchers say the flaw is especially dangerous when Gemini is given automatic access to Gmail and Google Calendar, because hidden instructions can alter appointments or instruct the agent to harvest sensitive inbox data. FireTail recommends disabling automatic email and calendar processing, constraining LLM actions, and monitoring responses while integrations are reviewed.

Google won’t fix new ASCII smuggling attack in Gemini

⚠️ Google has declined to patch a new ASCII smuggling vulnerability in Gemini, a technique that embeds invisible Unicode Tags characters to hide instructions from users while still being processed by LLMs. Researcher Viktor Markopoulos of FireTail demonstrated hidden payloads delivered via Calendar invites, emails, and web content that can alter model behavior, spoof identities, or extract sensitive data. Google said the issue is primarily social engineering rather than a security bug.

Google launches AI bug bounty program; rewards up to $30K

🛡️ Google has launched a new AI Vulnerability Reward Program to incentivize security researchers to find and report flaws in its AI systems. The program targets high-impact vulnerabilities across flagship offerings including Google Search, Gemini Apps, and Google Workspace core apps, and also covers AI Studio, Jules, and other AI integrations. Rewards scale with severity and novelty—up to $30,000 for exceptional reports and up to $20,000 for standard flagship security flaws. Additional bounties include $15,000 for sensitive data exfiltration and smaller awards for phishing enablement, model theft, and access control issues.

150 AI Use Cases from Startups Leveraging Google Cloud

🤖 At the AI Builders Forum, Google Cloud highlighted 150 startups using its generative AI stack—Vertex AI, Gemini, GKE, and Cloud Storage—to build agentic systems, healthcare models, developer tools, and media pipelines. The post catalogs companies across sectors (healthcare, finance, retail, security, creative) and describes technical integrations such as fine-tuning with Gemini, inference on GKE, and scalable analytics with BigQuery. It encourages startups to join Google for Startups Cloud and references a new Startup Technical Guide: AI Agents for building and scaling agentic applications.

Five Best Practices for Effective AI Coding Assistants

🛠️ This article presents five practical best practices to get better results from AI coding assistants. Based on engineering sprints using Gemini CLI, Gemini Code Assist, and Jules, the recommendations cover choosing the right tool, training models with documentation and tests, creating detailed execution plans, prioritizing precise prompts, and preserving session context. Following these steps helps developers stay in control, improve code quality, and streamline complex migrations and feature work.

Google advances AI security with CodeMender and SAIF 2.0

🔒 Google announced three major AI security initiatives: CodeMender, a dedicated AI Vulnerability Reward Program (AI VRP), and the updated Secure AI Framework 2.0. CodeMender is an AI-powered agent built on Gemini that performs root-cause analysis, generates self-validated patches, and routes fixes to automated critique agents to accelerate time-to-patch across open-source projects. The AI VRP consolidates abuse and security reward tables and clarifies reporting channels, while SAIF 2.0 extends guidance and introduces an agent risk map and security controls for autonomous agents.

Gemini Trifecta: Prompt Injection Exposes New Attack Surface

🔒 Researchers at Tenable disclosed three distinct vulnerabilities in Gemini's Cloud Assist, Search personalization, and Browsing Tool. The flaws let attackers inject prompts via logs (for example by manipulating the HTTP User-Agent), poison search context through scripted history entries, and exfiltrate data by causing the Browser Tool to send sensitive content to an attacker-controlled server. Google has patched the issues, but Tenable and others warn this highlights the risks of granting agents too much autonomy without runtime guardrails.

Dataproc ML library: Connect Spark to Gemini and Vertex

🔗 Google has released an open-source Python library, Dataproc ML, to streamline running ML and generative-AI inference from Apache Spark on Dataproc. The library uses a SparkML-style builder pattern so users can configure a model handler (for example, GenAiModelHandler) and call .transform() to apply Gemini or other Vertex AI models directly to DataFrames. It also supports loading PyTorch and TensorFlow model artifacts from GCS for large-scale batch inference and includes performance optimizations such as vectorized data transfer, connection reuse, and automatic retry/backoff.

Google Cloud Releases Generative Media Models on Vertex AI

🎨Google Cloud announced General Availability and feature updates for its generative media models on Vertex AI, including Gemini 2.5 Flash Image, Veo 3, Imagen 4, and Gemini 2.5 TTS. The release emphasizes production readiness and enterprise security while adding multi‑aspect ratio image generation, batch image processing, vertical 9:16 video formats with precise duration controls, and studio‑quality multi‑speaker text‑to‑speech across 70+ languages. These enhancements target teams seeking faster, controlled, and scalable cross‑format media workflows for sight, sound, and motion.