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Nov 11, 2026
Gemini Intelligence's November 10 update: Pixel 10 gets new features via Pixel Drop, motorola signature 27 is a November 19 U.S. preorder, and widgets and Android Auto are still coming
Google's November 10 Android announcement says Pixel 10, Pixel 10 Pro XL and Pixel 10 Pro Fold get the latest Gemini Intelligence features through that day's Pixel Drop. Motorola's first Gemini Intelligence phone, the motorola signature 27, is available for U.S. preorder on November 19, which is not a shipping date. Rambler is described as available on named Pixel 10 models and the Motorola phone, and task automation is expanding to the UK, India and Japan. Create My Widget, its Pixel Watch version and proactive Android Auto suggestions are still upcoming. Country, language, age, app, setup, Android version and usage conditions apply feature by feature, and some wording in the source is ambiguous.
Nov 10, 2026
Adobe and Google roadmap: PDF editing in Workspace, Gemini connectors, and Photoshop AI experiments
Adobe and Google announced an expanded partnership at Adobe MAX 2026, outlining three tiers of integration: Google models that Adobe says customers can already use, announced future pathways for Acrobat in Google Workspace and Gemini, and exploratory work with DeepMind on a Photoshop image model that could enable near-real-time edits. The roadmap separates what Adobe describes as available from what is planned or unconfirmed, but leaves rollout dates and included-plan details unspecified.
Nov 10, 2026
Gemini 4 Carbon opens paid API and Ultra access, introductory pricing ends November 30
Google has expanded Gemini 4 Carbon access beyond its initial cybersecurity defender program to paid API tiers and Google AI Ultra subscriptions. Developers can now use the frontier model through Google AI Studio and Gemini for business at an introductory rate of $2 per million input tokens and $10 per million output tokens—identical to Gemini 4 Argon pricing—until November 30, 2026, after which Carbon's price doubles to $4/$20 per million tokens. The model is positioned for complex multi-step coding, scientific reasoning, and cybersecurity workflows where deeper exploration justifies higher token consumption, while Argon remains recommended for most software engineering and knowledge work.