All news with #gemini tag

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.

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.