Google just accidentally published an experimental Android AI assistant called COSMO before quickly pulling it. Packed with an on-device Gemini Nano model at 1.13 GB, the app tested agentic skills like browser automation, Deep Research, and context recall. It offers an early glimpse into Android evolving into a proactive personal agent.
Google just announced its biggest Chrome upgrade yet, integrating Gemini directly across desktop and mobile. Users can now summarize multiple open tabs, recall past browsing via natural language, and search straight from the address bar, with autonomous agents for booking appointments coming soon. The rollout starts for U.S. desktop users in English.
Google just revealed nine new AI features for the Pixel 10 lineup, powered by the DeepMind-designed Tensor G5 chip and Gemini Nano. Standouts include Magic Cue for proactive cross-app suggestions, real-time voice-cloned call translation, and smart call handling. The push leans heavily into private, on-device intelligence that acts before you even ask.
Google just unveiled Gemma 3n, a mobile-first open model designed to run rich multimodal AI entirely on phones and laptops. Thanks to a new Per-Layer Embeddings technique, its 5B and 8B models operate with dynamic memory footprints of just 2GB and 3GB. Why it matters: it makes complex, private local AI actually fit on everyday hardware.
Google just detailed how it is deploying on-device AI across Search, Chrome, and Android to block evolving online scams. Desktop Chrome's Enhanced Protection mode now runs Gemini Nano locally to catch zero-day scam sites like fake remote tech support, while Android gains on-device warnings against rogue notifications, fraudulent texts, and suspicious calls.
Google just overhauled Android with a suite of new AI capabilities powered by Gemini and Circle to Search. Students can now circle math and physics problems for step-by-step explanations, while Gemini's new overlay can answer questions about YouTube videos. Even better, multimodal Gemini Nano will run on-device to spot phone scams in real time.
Apple just detailed how it plans to fit heavy AI models onto everyday devices without blowing past hardware limits. In a paper titled 'LLM in a flash', researchers store parameters on flash memory and stream them to DRAM on demand, running models twice the size of available RAM while speeding up GPU inference by up to 25x. Why it matters: It lays the technical groundwork for reliable on-device generative AI.
