During its Tuesday I/O event, Google disclosed that it is integrating its Gemini AI into Chrome on desktop. Gemini Nano, an on-device artificial intelligence feature that includes text creation, will be available in Chrome 126.

The tech giant's lightweight large language model (LLM), Gemini Nano, debuted in the Pixel 8 Pro last year, followed by the Pixel 8. Google modified the model and browser to speed up Chrome's AI functions.

Here's What to Know About Gemini Nano

Google's Gemini Nano runs on Android 14's AICore system-level capabilities, according to the company's blog. This function lets users access foundation models on their mobile devices.

AICore pre-installs foundation models, avoiding app downloads and distribution. LoRa lets developers customize these models. Google Pixel 8 Pro and Samsung S24 Series devices run Android AICore, which powers new Google app features.

This connection allows Chrome users to write product evaluations, social network postings, and other material. According to The Verge, last year, Microsoft integrated its AI helper Copilot into Edge. Notably, Gemini Nano runs locally on the user's device, unlike Copilot in Edge, which uses cloud services.

Google also revealed that Chrome DevTools, a package for debugging and optimizing apps, will include Gemini. Gemini will explain problem messages and recommend coding fixes.

Jon Dahlke, Google's Chrome director of product management, said Google is talking with other browser suppliers about allowing Gemini AI or a similar function. Dahlke said Tuesday that Google has begun engaging "with other browsers and will offer an "early preview program" for developers." "We think Chrome's webGPU, WASM, and Gemini make it AI-ready."

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Advantages of Google's Gemini Nano AI

AI models like Google's Gemini Nano run on devices, which has multiple benefits: In messaging apps with end-to-end encryption, local data processing improves privacy by avoiding cloud storage.

Moreover, applications that are intermittent or offline can benefit from offline access to AI features, and for commonly utilized user flows, offloading execution to consumer hardware can significantly save inference costs.

On-device Gemini Nano execution offers several benefits, but bigger Gemini models and more devices may necessitate server-based execution. Users can access the Gemini API via backend integration using Python, Go, Node.js, or REST or directly from Android apps using the new Google AI client SDK for Android.

This news about Gemini Nano follows an earlier TechTimes report that Google demonstrated ChromeOS on Android smartphones in a private business partner event, signaling the firm's ambitions to integrate the two platforms.

At the event, Google demonstrated ChromeOS on Android using the Android Virtualisation Framework. This solution requires connecting the smartphone to an external display to provide a safe and private execution environment, unlike Android's app sandbox.

According to the Android Authority, Google previously used Chromium OS to run a desktop OS on Android. The recent presentation implies that Google is moving toward a desktop-like Android smartphone experience, a widespread desire.

While details and dates for this integration are unknown, the presentation suggests Google may extend ChromeOS capability to Android devices, enabling smartphones to deliver a more computer-like experience.

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