All news with #gemini tag

🛡️ 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.

⚠️A representative YouGov survey commissioned by recruitment firm SThree found that 77% of STEM professionals in Germany use AI tools at work without approval from IT or management. Commonly used services include ChatGPT, Google Gemini and Perplexity. Experts warn this shadow IT practice can lead to GDPR breaches, inadvertent disclosure of sensitive customer or internal data and the risk that providers will retain and reuse submitted content for training. In Germany, 23% report daily use, 29% weekly and 12% monthly; respondents cite efficiency gains and technical curiosity as primary drivers.

🎨 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 has released Gemini 3 Pro, a multimodal model that posts strong benchmark results and produces notable real-world demos. Early tests show top-tier scores (LMArena 1501 Elo, high marks on MMMU-Pro and Video-MMMU) and PhD-level reasoning in targeted exams. Designers reported one-shot generation of a 3D LEGO editor and a full recreation of Ridiculous Fishing. Adherence remains imperfect, so the author suggests Claude Sonnet 4.5 for routine tasks and Gemini 3 Pro for more complex queries.

🔎 Google is testing AI-powered, interactive UI answers within AI Mode, integrating Gemini 3 to generate on-the-fly interfaces tailored to queries. Instead of relying solely on text and a couple of links, Search can produce dynamic tools—such as an RNA polymerase simulator—to demonstrate concepts in action. This change could improve comprehension but may also reduce traffic to original sites and reshape the web economy.

🛍️ Black Friday shopping is increasingly fraught with staged discounts and manipulated prices, but large language models (LLMs) can help shoppers cut through the noise. Use AI like ChatGPT, Claude, or Gemini to build a wish list, track historical prices, compare alternatives, and vet sellers quickly. The article provides step-by-step prompts for price analysis, seller verification, local-market queries, and model-specific requests, and recommends security measures such as using a separate card and installing Kaspersky Premium to reduce fraud risk.

🧬 This guide demonstrates step-by-step fine-tuning of MedGemma (a Gemma 3 variant) to classify breast histopathology images using the public BreakHis dataset and a notebook-based workflow. It highlights practical choices—using an NVIDIA A100 40 GB, switching from FP16 to BF16 to avoid numerical overflows, and employing LoRA adapters for efficient training. The tutorial reports dramatic accuracy gains after merging LoRA adapters and points readers to runnable notebooks for reproducibility.

🤖 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’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).