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Google Research introduces a new architecture using frozen Multi-Token Prediction to accelerate Gemini Nano models on Pixel devices, significantly improving speed and energy efficiency for on-device AI features.
A developer discovered Google's Gemini Nano 4B LLM built into Chrome and created an OpenAI-compatible API wrapper for local use, eliminating the need for API keys or external calls.
A developer created a Chrome extension called Dobby that runs Google's Gemma4 (Gemini Nano) locally on PC without needing a GPU, requiring only Chrome and 16GB RAM. The extension provides a simple interface to interact with the model for tasks like spell checking or summarizing.
Google Chrome is automatically downloading a 4GB Gemini Nano model weights file to users' devices to power on-device AI features like scam detection and writing assistance, often without clear notification about storage requirements. Users can disable the On-Device AI toggle in Chrome settings to remove the file and prevent re-downloads.
Google Chrome is silently installing a 4 GB Gemini Nano AI model on user devices without explicit consent or opt-out UI, raising significant privacy, legal, and environmental concerns.
Google announces Gemma 3n preview, a mobile-first open AI model optimized for on-device inference on phones, tablets, and laptops. Built on a new architecture developed with hardware partners like Qualcomm and MediaTek, Gemma 3n uses innovations like Per-Layer Embeddings to achieve fast performance with minimal memory footprint (2-3GB), while supporting multimodal capabilities.
Pixel Watch 3 & 4 introduce on-device ML for eyes-free double-pinch and wrist-flick gestures plus raise-to-talk Gemini activation without wake-words.