All news with #gemini tag

🎬 This guide introduces Veo 3.1, Google Cloud's improved generative video model available in preview on Vertex AI, and explains how to move beyond "prompt and pray" toward deliberate creative control. It highlights core capabilities—high-fidelity 720p/1080p output, variable clip lengths, synchronized dialogue and sound effects, and stronger image-to-video fidelity. The article presents a five-part prompting formula and detailed techniques for cinematography, soundstage direction, negative prompting, and timestamped scenes. It also describes advanced multi-step workflows that combine Gemini 2.5 Flash Image to produce consistent characters and controlled transitions, and notes SynthID watermarking and certain current limitations.

🔒 Google for Education highlights built-in security, responsible AI, and partnerships to create safer digital learning environments for schools, classrooms, and families. Admins benefit from automated 24/7 monitoring, encryption, spam filtering, and security alerts; Google reports zero successful ransomware attacks on Chromebooks to date. Gemini for Education and NotebookLM provide enterprise-grade data protections with admin controls and age-specific safeguards, while family resources and a $25M Google.org clinics fund extend protection and workforce development.

🔒 Google for Education outlines built-in security, responsible AI, and community investments for Cybersecurity Awareness Month 2025. The post highlights admin controls and automated protections—24/7 monitoring, encryption, and security alerts—and notes zero reported successful ransomware attacks on Chromebooks to date. It emphasizes Gemini for Education and NotebookLM with enterprise-grade data protections and stricter policies for students under 18. The company also supports workforce development through a $25 million Google.org fund and 25 cybersecurity clinics.

🔒 Google Security Operations has been named a Leader in the 2025 Gartner Magic Quadrant for SIEM, recognized for both Ability to Execute and highest Completeness of Vision. The AI-driven platform leverages Gemini to automate data analysis, assist investigations with natural language, and orchestrate responses, combining curated detections, SOAR, and case-centric workflows. Customers report measurable outcomes — up to 240% ROI over three years, 50% faster MTTR, and 65% faster MTTI — driven by automation and an emerging agentic SOC vision.

🔐 Gemini Code Assist on GitHub for enterprises delivers AI-powered code reviews across GitHub Enterprise Cloud and privately hosted GitHub Enterprise Server. Organization-level controls let platform teams define a central style guide, set comment severity, and enforce baseline checks while preserving repo-level customization. Built on Google Cloud security and privacy commitments, the public preview includes higher pull-request quotas and stateless prompt handling to protect customer code.

🚀 Google Cloud announced enhancements to NetApp Volumes, adding unified iSCSI block and file storage to support SAN migrations and NetApp FlexCache for high-performance local caching in hybrid environments. The service integrates with Gemini Enterprise as a data store for retrieval-augmented generation, and includes large-capacity volumes, SnapMirror replication, and auto-tiering to optimize performance and costs.

🤖 Google Cloud Marketplace offers a vetted path for organizations to deploy, buy, or build AI agents that integrate with Gemini Enterprise, simplifying procurement and deployment. Listings are pre-validated for A2A integration and allow consolidated billing, while administrators can enforce governance using IAM and Private Marketplace controls. For partners, the Marketplace provides global reach, co-selling, and flexible monetization (subscription, usage-based, private offers, outcome-based) plus automated provisioning via Pub/Sub and the Cloud Commerce Partner Procurement API.

🚀 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.

🚀 Google today launched Google Skills, a unified learning platform consolidating nearly 3,000 courses and labs from Google Cloud, Google DeepMind, Grow with Google and Google for Education. The rollout, timed with the release of Gemini Enterprise, integrates Gemini Code Assist into hands-on labs, introduces new skill badges, and adds gamified features and admin tools for organizations. A new GEAR sprint will target one million developers for agent development, and a partnership with Jack Henry creates a direct hiring pathway for U.S. certificate holders.

⚠️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 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’s DeepMind unveiled CodeMender, an AI agent that automatically detects, patches, and rewrites vulnerable code to remediate existing flaws and prevent future classes of vulnerabilities. Backed by Gemini Deep Think models and an LLM-based critique tool, it validates changes to reduce regressions and self-correct as needed. DeepMind says it has upstreamed 72 fixes to open-source projects so far and will engage maintainers for feedback to improve adoption and trust.

🔧 Google DeepMind has unveiled CodeMender, an autonomous agent built on Gemini Deep Think models that detects, debugs and patches complex software vulnerabilities. In the last six months it produced and submitted 72 security patches to open-source projects, including codebases up to 4.5 million lines. CodeMender pairs large-model reasoning with advanced program-analysis tooling — static and dynamic analysis, differential testing, fuzzing and SMT solvers — and a multi-agent critique process to validate fixes and avoid regressions. DeepMind says all patches are currently human-reviewed and it plans to expand maintainer outreach, release the tool to developers, and publish technical findings.

🛠️ 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.

🔒 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.

🔗 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 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.

🔎 The Gemini CLI extension for PostgreSQL brings natural-language queries and command-line convenience directly to database tasks. It can detect required tools (for example, pg_trgm for fuzzy search), check whether they are installed and install them automatically, and suggest performance improvements such as creating GIN or GIST indexes. The extension also generates schema-derived code snippets and supports lifecycle actions like creating instances, users, and permissions, streamlining development workflows.

🔒 Cybersecurity researchers disclosed three now-patched vulnerabilities in Google's Gemini suite that could have exposed user data and enabled search- and prompt-injection attacks. The flaws, labeled the Gemini Trifecta, impacted Gemini Cloud Assist, the Search Personalization model, and the Browsing Tool. Following responsible disclosure, Google stopped rendering hyperlinks in log summaries and implemented additional hardening. Tenable warned these issues could have allowed covert exfiltration of saved user information and location data.

⚠️Tenable has revealed three vulnerabilities in Google's Gemini platform, collectively dubbed the "Gemini Trifecta," that enable indirect prompt injection and data exfiltration through integrations. The issues allow attackers to poison GCP logs consumed by Gemini Cloud Assist, inject malicious entries into Chrome search history to manipulate the Search Personalization Model, and coerce the Browsing Tool into fetching attacker-controlled URLs that leak sensitive query data. Google has patched the flaws, and Tenable urges security teams to treat AI integrations as active threat surfaces and implement input sanitization, output validation, monitoring, and regular penetration testing.