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<\/p>\nPosted by Dave Burke, VP of Engineering<\/em><\/p>\n <\/p>\n Foundation Models learn from a diverse range of data sources to produce AI systems capable of adapting to a wide range of tasks, instead of being trained for a single narrow use case. Today, we announced Gemini<\/a>, our most capable model yet. Gemini was designed for flexibility, so it can run on everything from data centers to mobile devices. It’s been optimized for three different sizes: Ultra, Pro and Nano.<\/p>\n Gemini Nano, our most efficient model built for on-device tasks, runs directly on mobile silicon, opening support for a range of important use cases. Running on-device enables features where the data should not leave the device, such as suggesting replies to messages in an end-to-end encrypted messaging app. It also enables consistent experiences with deterministic latency, so features are always available even when there\u2019s no network.<\/p>\n Gemini Nano is distilled down from the larger Gemini models and specifically optimized to run on mobile silicon accelerators. Gemini Nano enables powerful capabilities such as high quality text summarization, contextual smart replies, and advanced proofreading and grammar correction. For example, the enhanced language understanding of Gemini Nano enables the Pixel 8 Pro to concisely summarize content in the Recorder app<\/a>, even when the phone\u2019s network connection is offline.<\/p>\n Gemini Nano is starting to power Smart Reply in Gboard on Pixel 8 Pro, ready to be enabled in settings as a developer preview<\/a>. Support in Android is rolling out for WhatsApp, Line, and KakaoTalk over the next few weeks with more messaging apps in the new year. The on-device AI model saves you time by suggesting high-quality responses with conversational awareness.1<\/sup>.<\/p>\n Android AICore<\/a> is a new system service in Android 14 that provides easy access to Gemini Nano. AICore handles model management, runtimes, safety features and more, simplifying the work for you to incorporate AI into your apps. <\/p>\n AICore is private by design, following the example of Android\u2019s Private Compute Core<\/a> with isolation from the network via open-source APIs, providing transparency and auditability. As part of our efforts to build and deploy AI responsibly, we also built dedicated safety features to make it safer and more inclusive for everyone.<\/p>\n AICore enables Low Rank Adaptation (LoRA) fine tuning with Gemini Nano. This powerful concept enables app developers to create small LoRA adapters based on their own training data. The LoRA adapter is loaded by AICore, resulting in a powerful large language model fine tuned for the app\u2019s own use-cases.<\/p>\n AICore takes advantage of new ML hardware like the latest Google Tensor TPU and NPUs in flagship Qualcomm Technologies, Samsung S.LSI and MediaTek silicon. AICore and Gemini Nano are rolling out to Pixel 8 Pro<\/a>, with more devices and silicon partners to be announced in the coming months.<\/p>\n We’re excited to bring together state-of-the-art AI research with easy-to-use tools and APIs for Android developers to build with Gemini on-device. If you are interested in building apps using Gemini Nano and AICore, please sign up for our Early Access Program<\/a>.<\/p>\n <\/p>\n![](\"https:\/\/blogger.googleusercontent.com\/img\/b\/R29vZ2xl\/AVvXsEil3wtlHfRLwD-JT5XKBGmS2Ml6syyISZ3sfnjy4gvUmYhoV_Mv4gPpAg_dc-VT3NOp6cM7YVBJMmjTxN360fn0IW-R2UtUctGqzl2tR9rVYtAgzn5yoh48PyznU3g_y2cEovfiysb3LYTT9dNzWyzlr58p9i25EVbX64AdLRrfnHc7q8KDUIWPD-dL3Es\/s1600\/Circle-droid@2x.png\")
<\/a><\/p>\nGemini Nano, optimized for mobile<\/h3>\n
<\/div>\n<\/div>\nAndroid AICore, a new system service for on-device foundation models<\/h3>\n
<\/div>\nBuild with Gemini<\/h3>\n