All news with #gemini tag

Vertex AI Context Caching: Reduce Cost and Latency

⚡ Vertex AI context caching saves and reuses precomputed input tokens so developers avoid repeatedly sending and recomputing long contextual content, reducing latency and cost for large-context AI applications. It provides implicit caching — automatic, default, short-lived KV caches (deleted within 24 hours) integrated with Provisioned Throughput — and explicit CachedContent objects that are paid once and then reused at a deep discount with optional CMEK protection. Caches support multimodal inputs and very large context windows.

Google Introduces Gemini Enterprise for the Workplace

🚀 Gemini Enterprise is presented as Google’s unified, enterprise-grade AI front door that integrates advanced models, a no-code workbench, pre-built and customizable agents, secure data connectors, centralized governance, and an open partner ecosystem. The chat-first interface works across Google Workspace and Microsoft 365 and adds multimodal agents for text, image, video, and speech. Google highlights developer tooling, open agent protocols, agent monetization, and customer deployments to accelerate end-to-end workflow automation and auditable governance.

Security firm urges disconnecting Gemini from Workspace

⚠️FireTail warns that Google Gemini can be tricked by hidden ASCII control characters — a technique the firm calls ASCII Smuggling — allowing covert prompts to reach the model while remaining invisible in the UI. The researchers say the flaw is especially dangerous when Gemini is given automatic access to Gmail and Google Calendar, because hidden instructions can alter appointments or instruct the agent to harvest sensitive inbox data. FireTail recommends disabling automatic email and calendar processing, constraining LLM actions, and monitoring responses while integrations are reviewed.

Google won’t fix new ASCII smuggling attack in Gemini

⚠️ Google has declined to patch a new ASCII smuggling vulnerability in Gemini, a technique that embeds invisible Unicode Tags characters to hide instructions from users while still being processed by LLMs. Researcher Viktor Markopoulos of FireTail demonstrated hidden payloads delivered via Calendar invites, emails, and web content that can alter model behavior, spoof identities, or extract sensitive data. Google said the issue is primarily social engineering rather than a security bug.

Google launches AI bug bounty program; rewards up to $30K

🛡️ Google has launched a new AI Vulnerability Reward Program to incentivize security researchers to find and report flaws in its AI systems. The program targets high-impact vulnerabilities across flagship offerings including Google Search, Gemini Apps, and Google Workspace core apps, and also covers AI Studio, Jules, and other AI integrations. Rewards scale with severity and novelty—up to $30,000 for exceptional reports and up to $20,000 for standard flagship security flaws. Additional bounties include $15,000 for sensitive data exfiltration and smaller awards for phishing enablement, model theft, and access control issues.

150 AI Use Cases from Startups Leveraging Google Cloud

🤖 At the AI Builders Forum, Google Cloud highlighted 150 startups using its generative AI stack—Vertex AI, Gemini, GKE, and Cloud Storage—to build agentic systems, healthcare models, developer tools, and media pipelines. The post catalogs companies across sectors (healthcare, finance, retail, security, creative) and describes technical integrations such as fine-tuning with Gemini, inference on GKE, and scalable analytics with BigQuery. It encourages startups to join Google for Startups Cloud and references a new Startup Technical Guide: AI Agents for building and scaling agentic applications.

Five Best Practices for Effective AI Coding Assistants

🛠️ This article presents five practical best practices to get better results from AI coding assistants. Based on engineering sprints using Gemini CLI, Gemini Code Assist, and Jules, the recommendations cover choosing the right tool, training models with documentation and tests, creating detailed execution plans, prioritizing precise prompts, and preserving session context. Following these steps helps developers stay in control, improve code quality, and streamline complex migrations and feature work.

Google advances AI security with CodeMender and SAIF 2.0

🔒 Google announced three major AI security initiatives: CodeMender, a dedicated AI Vulnerability Reward Program (AI VRP), and the updated Secure AI Framework 2.0. CodeMender is an AI-powered agent built on Gemini that performs root-cause analysis, generates self-validated patches, and routes fixes to automated critique agents to accelerate time-to-patch across open-source projects. The AI VRP consolidates abuse and security reward tables and clarifies reporting channels, while SAIF 2.0 extends guidance and introduces an agent risk map and security controls for autonomous agents.

Gemini Trifecta: Prompt Injection Exposes New Attack Surface

🔒 Researchers at Tenable disclosed three distinct vulnerabilities in Gemini's Cloud Assist, Search personalization, and Browsing Tool. The flaws let attackers inject prompts via logs (for example by manipulating the HTTP User-Agent), poison search context through scripted history entries, and exfiltrate data by causing the Browser Tool to send sensitive content to an attacker-controlled server. Google has patched the issues, but Tenable and others warn this highlights the risks of granting agents too much autonomy without runtime guardrails.

Dataproc ML library: Connect Spark to Gemini and Vertex

🔗 Google has released an open-source Python library, Dataproc ML, to streamline running ML and generative-AI inference from Apache Spark on Dataproc. The library uses a SparkML-style builder pattern so users can configure a model handler (for example, GenAiModelHandler) and call .transform() to apply Gemini or other Vertex AI models directly to DataFrames. It also supports loading PyTorch and TensorFlow model artifacts from GCS for large-scale batch inference and includes performance optimizations such as vectorized data transfer, connection reuse, and automatic retry/backoff.

Google Cloud Releases Generative Media Models on Vertex AI

🎨Google Cloud announced General Availability and feature updates for its generative media models on Vertex AI, including Gemini 2.5 Flash Image, Veo 3, Imagen 4, and Gemini 2.5 TTS. The release emphasizes production readiness and enterprise security while adding multi‑aspect ratio image generation, batch image processing, vertical 9:16 video formats with precise duration controls, and studio‑quality multi‑speaker text‑to‑speech across 70+ languages. These enhancements target teams seeking faster, controlled, and scalable cross‑format media workflows for sight, sound, and motion.

Accelerate AI with Agents: EMEA Developer Series and Labs

🚀 Google Cloud is hosting a regional event series across EMEA to help developers and tech practitioners learn to build and scale AI agents. The program combines immersive, hands-on labs and expert-led workshops covering technologies such as Cloud Run, Vertex AI, Gemini, and the Agent Development Kit (ADK). Participants receive step-by-step guidance and practical exercises designed to accelerate agent deployments and operational readiness within organizations.

Researchers Disclose Trio of Gemini AI Vulnerabilities

🔒 Cybersecurity researchers disclosed three now-patched vulnerabilities in Google's Gemini suite that could have exposed user data and enabled search- and prompt-injection attacks. The flaws, labeled the Gemini Trifecta, impacted Gemini Cloud Assist, the Search Personalization model, and the Browsing Tool. Following responsible disclosure, Google stopped rendering hyperlinks in log summaries and implemented additional hardening. Tenable warned these issues could have allowed covert exfiltration of saved user information and location data.

Gemini Trifecta Exposes Indirect AI Attack Surfaces

⚠️Tenable has revealed three vulnerabilities in Google's Gemini platform, collectively dubbed the "Gemini Trifecta," that enable indirect prompt injection and data exfiltration through integrations. The issues allow attackers to poison GCP logs consumed by Gemini Cloud Assist, inject malicious entries into Chrome search history to manipulate the Search Personalization Model, and coerce the Browsing Tool into fetching attacker-controlled URLs that leak sensitive query data. Google has patched the flaws, and Tenable urges security teams to treat AI integrations as active threat surfaces and implement input sanitization, output validation, monitoring, and regular penetration testing.

Advanced Threat Hunting with LLMs and the VirusTotal API

🛡️ This post summarizes a hands-on workshop from LABScon that demonstrated automating large-scale threat hunting by combining the VirusTotal API with LLMs inside interactive Google Colab notebooks. The team recommends vt-py for robust programmatic access and provides a pre-built "meta Colab" that supplies Gemini with documentation and working code snippets so it can generate executable Python queries. Practical demos include LNK and CRX analyses, flattened dataframes, Sankey and choropleth visualizations, and stepwise relationship retrieval to accelerate investigations.

INDOT Used Google AI to Save 360 Hours and Meet Deadline

🚀 Indiana Department of Transportation built a week-long pilot on Google Cloud to meet a 30-day executive order, using a Retrieval-Augmented Generation workflow that combined rapid ETL, Vertex AI Search indexing, and Gemini. The system scraped and parsed decades of internal policies and manuals, produced draft reports across nine divisions with 98% fidelity, and saved an estimated 360 hours of manual effort, enabling INDOT to submit on time.

Gemini in Chrome: Secure AI for Enterprise Productivity

🤖 Gemini in Chrome brings AI assistance directly into the browser to help employees summarize reports, extract video insights, recall and navigate tabs, and take actions via integrations with Google Calendar, Docs, and Drive. Rolling out in the U.S. on Mac and Windows with Android availability and iOS coming soon, these features are configurable through Chrome Enterprise Core policies so IT retains control. AI Mode in the omnibox and enhanced Safe Browsing add context-aware responses and proactive protection against AI-driven scams.

Seattle Children’s Uses AI to Accelerate Pediatric Care

🤖 Seattle Children’s partnered with Google Cloud to build Pathway Assistant, a multimodal AI chatbot that turns thousands of pediatric clinical pathway PDFs into conversational, searchable guidance. Using Vertex AI and Gemini, the assistant extracts JSON metadata, parses diagrams and flowcharts, and returns cited answers in seconds. The tool logs clinician feedback to BigQuery and stores source documents in Cloud Storage, enabling continuous improvement of documentation and metadata.

Google Cloud's Differentiated AI Stack Fuels Startups

🚀 Google Cloud highlights how its differentiated AI tech stack is accelerating startup innovation worldwide, with nine of the top ten AI labs, most AI unicorns, and more than 60% of generative AI startups using its platform. Startups are leveraging Vertex AI, TPUs, multimodal models like Veo 3 and Gemini, plus services such as AI Studio and GKE to build agents, generative media, medical tools, and developer platforms. Programs like the Google for Startups Cloud Program provide credits, mentorship, and engineering support to help founders scale.

Gemini and Open-Source Text Embeddings Now in BigQuery ML

🚀 Google expanded BigQuery ML to generate embeddings from Gemini and over 13,000 open-source text-embedding models via Hugging Face, all callable with simple SQL. The post summarizes model tiers to help teams trade off quality, cost, and scalability, and introduces Gemini's Tokens Per Minute (TPM) quota for throughput control. It shows a practical workflow to deploy OSS models to Vertex AI endpoints, run ML.GENERATE_EMBEDDING for batch jobs, and undeploy to minimize idle costs, plus a Colab tutorial and cost/scale guidance.