All news with #gemini tag

Nano Banana Pro: Gemini 3 Pro Image for Enterprise Use

🎨 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's Gemini 3 Pro Impresses with One‑Shot Game Creation

🎮 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 Search Tests AI-Generated Interactive UI Answers

🔎 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.

Using AI to Avoid Black Friday Price Manipulation and Scams

🛍️ 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.

Google Gemini 3 Appears on AI Studio Ahead of Release

🤖 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).

Production-Ready AI with Google Cloud Learning Path

🚀 Google Cloud has launched the Production-Ready AI Learning Path, a free curriculum designed to guide developers from prototype to production. Drawing on an internal playbook, the series pairs Gemini models with production-grade tools like Vertex AI, Google Kubernetes Engine, and Cloud Run. Modules cover LLM app development, open model deployment, agent building, security, RAG, evaluation, and fine-tuning. New modules will be added weekly through mid-December.

Advancing Text-to-SQL: Gemini's BIRD Benchmark Breakthrough

🚀 Google Cloud reports a new state-of-the-art Single Trained Model Track score on the BIRD benchmark, achieving 76.13 with a fine-tuned Gemini 2.5-pro. The team credits rigorous data filtering, multitask supervised fine-tuning, and test-time self-consistency selection for the gains. These improvements bolster NL2SQL features in AlloyDB AI and BigQuery, and enhance developer tooling such as Gemini Code Assist for reliable SQL generation.

Agent Factory Recap: Building Open Agentic Models End-to-End

🤖 This recap of The Agent Factory episode summarizes a conversation between Amit Maraj and Ravin Kumar (DeepMind) about building open-source agentic models. It highlights how agent training differs from standard ML, emphasizing trajectory-based data, a two-stage approach of supervised fine-tuning followed by reinforcement learning, and the paramount role of evaluation. Practical guidance includes defining a 50-example final exam up front and considering hybrid setups that use a powerful API like Gemini as a router alongside specialized open models.

Looker Conversational Analytics Reaches General Availability

💬 Google Cloud has made Looker Conversational Analytics generally available, bringing natural-language data queries to all Looker users. Built on the Looker semantic layer and powered by Gemini and Google’s agentic frameworks, the feature provides instant, explainable answers and supports multi-turn exploration across up to five connected Explores. Analysts can build and share agents, use LookML for fine tuning, and rely on a governed foundation that surfaces “How was this calculated?” explanations. Admins can enable the capability now to accelerate data discovery and improve self-service across teams.

BigQuery AI Functions: Reimagining SQL for the AI Era

🤖 BigQuery is introducing managed AI functions in public preview — AI.IF, AI.CLASSIFY, and AI.SCORE — that let analysts apply generative AI directly inside SQL queries. These functions enable semantic filtering and joins, label-based classification of text and images, and natural-language ranking, while BigQuery applies prompt, query-plan, and endpoint optimizations to reduce LLM calls and control cost. They complement existing Gemini inference functions and remove much of the need for complex prompt tuning or separate model selection, making AI-driven analytics more accessible within familiar SQL workflows.

Bringing Connected AI Work Experiences Across Devices

🚀 Google outlines its plan to embed Generative AI across enterprise platforms and endpoints, integrating Gemini into Chrome Enterprise, Android, Pixel phones and Chromebook Plus devices. The post highlights the general availability of Cameyo by Google to virtualize legacy and modern apps in the cloud and the launch of Gemini in Chrome with enterprise-grade controls. It also previews Android XR and Pixel features powered by Gemini Nano, while expanding data loss prevention and a one-click SecOps integration to help IT secure AI-driven workflows.

Google Cloud Expands AI Infrastructure and Services in India

🤝 Google Cloud is increasing local AI compute in India with its AI Hypercomputer powered by Trillium TPUs, enabling training and serving of advanced Gemini models with data residency and sovereignty controls. New local offerings include batch support for Gemini 2.5 Flash, a preview of Document AI, and real‑time grounding using Google Maps for location‑aware responses. Google is also supporting Indic Arena at IIT Madras with cloud credits to benchmark Indian multilingual models and to help grow the local AI ecosystem.

Leak: Google Gemini 3 Pro and Nano Banana 2 Launch Plans

🤖 Google appears set to release two new models: Gemini 3 Pro, optimized for coding and general use, and Nano Banana 2 (codenamed GEMPIX2), focused on realistic image generation. Gemini 3 Pro was listed on Vertex AI as "gemini-3-pro-preview-11-2025" and is expected to begin rolling out in November with a reported 1 million token context window. Nano Banana 2 was also spotted on the Gemini site and could ship as early as December 2025.

Agent Factory Recap: Build AI Apps in Minutes with Google

🤖 This recap of The Agent Factory features Logan Kilpatrick from Google DeepMind demonstrating vibe coding in Google AI Studio, a Build workflow that turns a natural-language app idea into a live prototype in under a minute. Live demos included a virtual food photographer, grounding with Google Maps, the AI Studio Gallery, and a speech-driven "Yap to App" pair programmer. The episode also surveyed agent ecosystem updates—Veo 3.1, Anthropic Skills, and Gemini improvements—and highlighted the shift from models to action-capable systems.

AI-Powered Malware Emerges: Google Details New Threats

🛡️ Google Threat Intelligence Group (GTIG) reports that cybercriminals are actively integrating large language models into malware campaigns, moving beyond mere tooling to generate, obfuscate, and adapt malicious code. GTIG documents new families — including PROMPTSTEAL, PROMPTFLUX, FRUITSHELL, and PROMPTLOCK — that query commercial APIs to produce or rewrite payloads and evade detection. Researchers also note attackers use social‑engineering prompts to trick LLMs into revealing sensitive guidance and that underground marketplaces increasingly offer AI-enabled “malware-as-a-service,” lowering the bar for less skilled threat actors.

Build Your First AI Travel Assistant with Gemini Today

🚀 This codelab walks developers through building a functional travel chatbot using Google's Gemini via the Vertex AI SDK. It explains how to connect a web frontend to Gemini, craft system instructions to shape assistant behavior, and enable function-calling to fetch live data such as geocoding and weather. No advanced ML expertise is required; the lab provides step-by-step code samples, API usage, and practical recommendations for iterating prompts so you can produce a working, production-ready demo.

Google: LLMs Employed Operationally in Malware Attacks

🤖 Google’s Threat Intelligence Group (GTIG) reports attackers are using “just‑in‑time” AI—LLMs queried during execution—to generate and obfuscate malicious code. Researchers identified two families, PROMPTSTEAL and PROMPTFLUX, which query Hugging Face and Gemini APIs to craft commands, rewrite source code, and evade detection. GTIG also documents social‑engineering prompts that trick models into revealing red‑teaming or exploit details, and warns the underground market for AI‑enabled crime is maturing. Google says it has disabled related accounts and applied protections.

Google: PROMPTFLUX malware uses Gemini to self-write

🤖 Google researchers disclosed a VBScript threat named PROMPTFLUX that queries Gemini via a hard-coded API key to request obfuscated VBScript designed to evade static detection. A 'Thinking Robot' component logs AI responses to %TEMP% and writes updated scripts to the Windows Startup folder to maintain persistence. Samples include propagation attempts to removable drives and mapped network shares, and variants that rewrite their source on an hourly cadence. Google assesses the malware as experimental and currently lacking known exploit capabilities.

October 2025 Google AI: Research, Products, and Security

📰 In October, Google highlighted AI advances across research, consumer devices and enterprise tools, from rolling out Gemini for Home and vibe coding in AI Studio to launching Gemini Enterprise for workplace AI. The month included security initiatives for Cybersecurity Awareness Month—anti‑scam protections, CodeMender and the Secure AI Framework 2.0—and developer releases like the Gemini 2.5 Computer Use model. Research milestones included a verifiable quantum advantage result and an oncology-focused model, Cell2Sentence-Scale, aimed at accelerating cancer therapy discovery.

BigQuery's Data Engineering Agent: Automating Pipelines

🔧 The preview of the Data Engineering Agent in BigQuery introduces a Gemini-powered assistant that automates pipeline development, maintenance, and migrations. The agent converts natural-language requirements into SQL, enforces engineering best practices, and supports custom instructions and UDFs to reflect organizational logic. Integrated with Dataplex, it uses governance metadata to improve table descriptions, data quality assertions, and PII-aware handling, and it also generates documentation and troubleshooting guidance. The feature is available in preview via BigQuery Pipelines and the Dataform UI.