All news with #gemini tag

🚨 Google Workspace with Gemini helps agencies convert complex, legally precise emergency documents into clear, actionable public-facing tools almost instantly. By parsing executive orders to extract locations, curfews, and exemptions and generating interactive prototypes or safety-check interfaces directly in the conversation window, the system shortens deployment from days to minutes. Built with public-sector security like FedRAMP High, data residency controls, DLP, and client-side encryption, it provides a repeatable blueprint for rapid, trustworthy disaster response.

🔊 The post announces general availability of Gemini Live API on Vertex AI, powered by the Gemini 2.5 Flash Native Audio model. It presents a unified, low-latency native audio architecture that replaces multi-stage STT/LLM/TTS pipelines and enables real-time multimodal reasoning over audio, text, and visual streams via a stateful WebSocket. Two quickstart templates (Vanilla JS and React) and three production demos illustrate common integration patterns, partner telephony/WebRTC support, and recommended backend proxying for secure credentials.

🔗 This post explains how to expose Looker’s semantic layer to Gemini Enterprise quickly by using the MCP Toolbox for Databases and the Agent Development Kit (ADK). It outlines three concise steps: deploy the MCP Toolbox (recommended to Cloud Run), build and deploy an ADK agent to Vertex AI Agent Engine, and register that agent with Gemini Enterprise. The result: trusted Looker models available inside Gemini for natural‑language business queries.

🔹Google's Data Cloud presents an AI-native approach to unify siloed, multimodal enterprise data and enable real-time insights. The platform integrates Gemini with BigQuery to automate pipeline building, vector embedding, and data quality, while Dataplex provides continuous cataloging and contextual metadata for agents. Enhancements to managed streaming, Pub/Sub UDFs, and Dataflow extend real-time processing, governance, and developer productivity.

🔊 Gemini Live API, powered by the Gemini 2.5 Flash Native Audio model, is now generally available on Vertex AI. It enables low-latency, multimodal conversational agents that combine voice, vision, and text to deliver human-like, contextual interactions. The API supports natural turn-taking, acoustic cue analysis, and visual understanding, and is optimized for enterprise-scale, regional deployments and compliance. Early adopters including Shopify, United Wholesale Mortgage, and SightCall report improved efficiency and real-time assistance.

🔒 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.

🧭 This episode of The Agent Factory unpacks Google's latest AI stack—Gemini 3, the Antigravity IDE, and Nano Banana Pro—through hands-on demos and developer commentary. Guests demonstrate end-to-end workflows, from generating a React Native cataloging app to refactoring a site from screenshots and producing game assets with grounded search. The recap emphasizes enhanced tool use, multimodal inputs, and smoother deployment to Google Cloud. It also highlights the new Vending Bench metric for agentic, long-range decision-making.

🔬 AlphaEvolve is a Gemini-powered coding agent on Google Cloud that automates evolutionary optimization of algorithms for complex, code-defined problems. It takes a problem specification, evaluation logic, and a compile-ready seed program, then uses Gemini models to propose mutated code variants and an evolutionary framework to select and refine the best candidates. Early internal results at Google demonstrate measurable efficiency improvements, and the AlphaEvolve Service API is available through a private Early Access Program for interested organizations.

🛡️ Google has added a separate user alignment critic to its Gemini-powered Chrome browsing agent to vet and block proposed actions that do not match user intent. The critic is isolated from web content and sees only metadata about planned actions, providing feedback to the primary planning model when it rejects a step. Google also enforces origin sets to limit where the agent can read or act, requires confirmations for banking, medical, password use and purchases, and runs a classifier plus automated red‑teaming to detect prompt injection attempts during preview.

🛡️ Google is introducing a new defense layer in Chrome called User Alignment Critic to protect upcoming agentic browsing features powered by Gemini. The isolated secondary LLM operates as a high‑trust system component that vets each action the primary agent proposes, using deterministic rules, origin restrictions and a prompt‑injection classifier to block risky or irrelevant behaviors. Chrome will pause for user confirmation on sensitive sites, run continuous red‑teaming and push fixes via auto‑update, and is offering bounties to encourage external testing.

🛡️ Chrome describes a layered approach to secure agentic browsing with Gemini, focusing on defenses against indirect prompt injection and goal‑hijacking. A new User Alignment Critic — an isolated, high‑trust model — reviews planned agent actions using only metadata and can veto misaligned steps. Chrome also enforces Agent Origin Sets to limit readable and writable origins, adds deterministic confirmations for sensitive actions, runs prompt‑injection detection in real time, and sustains continuous red‑teaming and monitoring to reduce exfiltration and unwanted transactions.

🔐 This post from Adrien Delaroche at Google Cloud outlines three architectures for AI agents that interact with blockchains: the agent-controlled custodial model, a self-hosted variant, and the non-custodial transaction-crafter model. It explains security, performance, and malice risks when agents hold private keys and recommends returning unsigned transactions so users sign locally. The author demonstrates a sample implementation using Google ADK, Gemini 2.0 Flash, Cloud Run, and an Ethereum faucet, and urges MCP servers to support both signing and unsigned flows to balance automation with user safety.

🧬 Combining Google’s ADK, Gemini, and Cloud infrastructure, this work reframes variant interpretation as a conversational workflow that removes repetitive scripting and context switching. A two-phase design performs heavy VEP annotation once, stores versioned ADK artifacts and public BigQuery datasets, and enables sub-5-second interactive queries via a QueryAgent. Validation with an APOB spike-in demonstrated single-variant precision, compatibility across DeepVariant versions, and scalability to ~8.8M variants.

🎧 In episode 79 of The AI Fix, hosts Graham Cluley and Mark Stockley examine the latest surprises from Gemini 3, including boastful comparisons, hallucinations about the year, and reactions from industry players. They also discuss an arXiv paper proposing adversarial poetry as a universal jailbreak for LLMs and the ensuing debate over its provenance. Additional segments cover robot-versus-appliance antics, a controversial AI teddy pulled from sale after disturbing interactions with children, and whether humans need safer robots — or stricter oversight.

🚀 The GKE Turns 10 Hackathon showcased developer teams building agentic AI on GKE integrated with Google models such as Gemini. More than 4,700 participants from 133 countries produced 133 projects demonstrating multi-agent pipelines, model orchestration, and microservice integration. Grand prize winner Amie Wei’s Cart-to-Kitchen assistant uses GKE Autopilot, the Agent Development Kit (ADK), and Agent-to-Agent protocols to analyze grocery carts and recommend recipes. Google also announced GEAR, an educational sprint launching in early 2026 to help developers learn, build, and deploy AI agents.

🚧 Gemini 3’s release on 18 November 2025 signals a structural shift: beyond headline performance gains, it accelerates embedding large multimodal assistants directly into enterprise workflows and infrastructure. That continuation of a trend already visible with Microsoft Copilot effectively makes AI assistants a new enterprise perimeter — changing where corporate data, identities, and controls must be enforced. Security, compliance, and IT teams need to update policies, telemetry, and incident response to this expanded boundary.

🚀 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.

🚀 The Gemini CLI now includes Looker and Looker Conversational Analytics extensions, enabling direct terminal access to Looker data and dashboards. These additions let users ask complex questions, generate reports, and create dashboards without leaving the command line. Installation requires the Gemini CLI (npm), the two extensions, and configuration of Looker API credentials and optional Google Cloud settings. The update aims to streamline workflows and make data exploration more accessible from everyday development environments.

🔬 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.

🤖Google has begun showing ads in its AI mode, the company's answer-engine experience rather than a traditional search engine. AI mode has been available for about a year and is free to all, with Google One subscribers able to toggle advanced models such as Gemini 3 Pro. Until now Google avoided ads to keep the conversational experience compelling; the new placements are labeled “sponsored” and typically appear at the bottom of AI-generated answers rather than in the right-side citation area. This looks like an experiment or optimization to improve click-through rates while complying with ad disclosure rules.