All news with #gemini tag

🤖 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.

🤖 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.

🤖 Google’s open-source Agent Development Kit (ADK) simplifies creating autonomous AI agents that use LLMs such as Gemini as their reasoning core. The post presents three hands-on codelabs that guide developers through building a personal assistant agent, adding custom and third-party tools, and orchestrating multi-agent workflows. Each lab demonstrates practical patterns—scaffolding an agent, integrating tools like Google Search and LangChain components, and using Workflow Agents and session state to pass information—so teams can progress from experiment to production-ready agent systems.

🚀 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 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.

📰 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.

🤖 October updates feature major product releases, developer tools, and research milestones from Google, centered on Gemini models and new AI capabilities. Highlights include Gemini Enterprise, the Gemini 2.5 Computer Use model for UI agents, plus consumer integrations such as Gemini for Home and Samsung's Galaxy XR. The month also brought breakthroughs in quantum computing, cancer research (Cell2Sentence-Scale) and fusion-energy collaborations, alongside expanded AI security measures and developer learning resources.

🔬 Google Cloud presents how researchers can accelerate scientific workflows by combining Gemini Enterprise with integrated HPC infrastructure. It showcases AI agents—like the Deep Research agent for literature synthesis and the Idea Generation agent for proposing and ranking hypotheses—alongside developer tooling such as Gemini Code Assist and Gemini CLI for code, debugging, and workflow automation. The platform pairs these capabilities with purpose-built VMs (H4D, A4, A4X) and Google Cloud Managed Lustre to scale simulations and analysis.

📣Google says its ad business will remain central as it integrates advertising into AI-powered search experiences. Google currently offers AI Overviews and a more capable AI Mode, and has begun limited experiments placing ads within those results. Executives say ads won't disappear but may appear differently and become more personalized based on user data. Tests and further plans are expected to continue into next year.

🚀 Google has open-sourced the GKE Gemini CLI extension, bringing Google Kubernetes Engine directly into the Gemini CLI ecosystem while also functioning as an MCP server for other MCP clients. The extension injects GKE-specific context, tools, and tailored prompts so developers can use shorter, more natural language interactions and integrated slash commands to complete complex workflows. It simplifies common operations—like selecting models and accelerators or generating Kubernetes manifests for inference—while improving compatibility with Cloud Observability. The project is actively maintained with regular releases and community contributions.

🤖 The new Jules extension for Gemini CLI lets developers delegate routine engineering tasks—like bug fixes, dependency updates, and vulnerability patches—to an autonomous background agent. Jules runs asynchronously and can work on multiple GitHub issues in parallel, preparing fixes in isolated environments for review. It also composes with other extensions to automate security remediation, crash investigation, and unit test creation, returning ready-to-review branches so you can stay focused on higher-value work.

📚 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.

🔁 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.

🔍 The episode of The Agent Factory reviewed practical AI agents for data engineering and data science, highlighting demos that combine Gemini, BigQuery, Colab Enterprise, and Spanner-based graph queries. It showcased a BigQuery Data Engineering Agent that generates pipelines, time dimensions, and data-quality assertions from SQL, and a Data Science Agent that runs end-to-end anomaly detection in Colab. The post also covered CodeMender for autonomous code security fixes and a creative Spanner+ADK comic demo illustrating multi-region concepts.

🎨 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.

🔬 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.

🚀 Google has released the Google Gen AI .NET SDK, bringing unified access to Gemini on Google AI and Vertex AI for C#/.NET developers. The SDK is available via NuGet (dotnet add package Google.GenAI) and supports client creation with an API key or with project/location settings for Vertex AI. Examples demonstrate unary and streaming text generation, image generation, and configurable response schemas and generation settings. Google provides the API reference, GitHub source (googleapis/dotnet-genai) and a DemoApp with samples to help developers get started.

🔍 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.

🧠 In episode 73 of The AI Fix, hosts Graham Cluley and Mark Stockley explore a sweep of recent AI developments, from the rise of AI-generated content to high-profile figures relying on chatbots. They discuss research suggesting Google Gemini exhibits behaviours resembling pathological gambling and report on a Gemma-style model uncovering a potential cancer therapy pathway. The show also highlights legal and security concerns— including a lawyer criticised for repeated AI use, generals consulting chatbots, and techniques for poisoning LLMs with only a few malicious samples.

🏆 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.