Posted by Joseph Lewis – Technical Writer, Android AI
AI on Android Spotlight Week this year runs September 30th to October 4th! As part of the Android “Spotlight Weeks” series, this week’s content and updates are your gateway to understanding how to integrate cutting-edge AI into your Android apps. Whether you’re a seasoned Android developer, an AI enthusiast, or just starting out on your development journey, get ready for a week filled with insightful sessions, practical demos, and inspiring success stories that’ll help you build intuitive and powerful AI integrations.
Throughout the week, we’ll dive into the core technologies driving AI experiences on Android. This blog will be updated throughout the week with links to new announcements and resources, so check back here daily for updates!
Monday: Getting started with AI
September 30, 2024
Learn how to begin with AI on Android development. Understand which AI models and versions you can work with. Learn about developer tools to help you start building features empowered with AI.
We’ll guide you through the differences between traditional programming and machine learning, and contrast traditional machine learning with generative AI. The post explains large language models (LLMs), the transformer architecture, and key concepts like context windows and embeddings. It also touches on fine-tuning and the future of LLMs on Android.
Read the blog post: A quick introduction to large language models for Android Developers
We’ll then provide a look behind the scenes at our work improving developer productivity with Gemini in Android Studio. We’ll discuss Studio’s new AI code completion feature, how we’ve been working to improve the accuracy and quality of suggested code, and how this feature can benefit your workflow.
Read the blog post: Gemini in Android Studio: Code Completion gains powerful model improvements
Tuesday: On-device AI capabilities with Gemini Nano
October 1, 2024
Discover how Gemini Nano empowers Android developers to unlock the full potential of generative AI, offering personalization and privacy benefits for next-generation apps. We’ll share how you can begin integrating your Android apps with on-device LLMs. Look for more information and announcements here on Tuesday!
Wednesday: On-device AI with custom models
October 2, 2024
On Wednesday, we’ll help you understand how to bring your own AI model to Android devices, and how you can integrate tools and technologies from Google and other sources. The ability to run sophisticated AI models directly on devices – whether it’s a smartphone, tablet, or embedded system – opens up exciting possibilities for better performance, privacy, usability, and cost efficiency.
We’ll also give you a detailed walkthrough of how Android developers can leverage Google AI Edge Torch to convert PyTorch machine learning models for on-device execution, using the LiteRT and MediaPipe Tasks libraries. This walkthrough includes code examples and explanations for converting a MobileViT model for image classification and a DIS model for segmentation, and highlights the steps involved in preparing these models for seamless integration into Android applications. By following this guide, developers can harness PyTorch models to enhance their Android apps with advanced machine learning capabilities.
Thursday: Access cloud models with Android SDKs
October 3, 2024
Tap into the boundless potential of Gemini 1.5 Pro and Gemini 1.5 Flash, the revolutionary generative AI models that are redefining the capabilities of Android apps. With Gemini 1.5 Pro and 1.5 Flash, you’ll have the tools you need to create apps that are truly intelligent and interactive.
On Thursday, we’ll give you a codelab that’ll help you understand how to integrate the Gemini API capabilities into your Android projects. We’ll guide you through crafting effective prompts and integrate Vertex AI in Firebase. By the end of this hands-on tutorial, you’ll be able to implement features like text summarization in your own app all powered by the cutting-edge Gemini models.
Next we’ll publish a blog post exploring the potential of the Gemini API with case studies. We’ll delve into how Android developers are leveraging generative AI capabilities in innovative ways, showcasing real-world examples of apps that have successfully integrated the Gemini API. From meal planning to journaling and personalized user experiences, the article highlights examples of how Android developers are already taking advantage of Gemini transformative capabilities in their apps.
We’ll also share with you examples of advanced features of the Gemini API to go beyond simple text prompting. You’ll learn how system instructions can shape the model behavior, how JSON support streamlines development, and how multimodal capabilities and function calling can unlock exciting new use cases for your apps.
Friday: Build with AI on Android and beyond
October 4, 2024
As the capstone for AI on Android Spotlight Week, we’ll host a discussion with Kateryna Semenova, Oli Gaymond, Miguel Ramos, and Khanh LeViet to talk about building with AI on Android. We’ll explore the latest AI advancements tailored for Android engineers, showcasing how these technologies can elevate your app development game. Through engaging discussions and real-world examples, we will unveil the potential of AI, from fast, private on-device solutions using Gemini Nano to the powerful capabilities of Gemini 1.5 Flash and Pro. We’ll discuss building generative AI solutions rapidly using Vertex AI in Firebase. And we’ll dive into harnessing the power of AI with safety and privacy in mind.
Work with Gemini beyond Android
As we wrap things up for AI on Android Spotlight Week, know that we’re striving to provide comprehensive AI solutions for cross-platform Gemini development. The AI capabilities showcased during Android AI Week can extend to other platforms, such as built-in AI in Chrome. Web developers can leverage similar tools and techniques to create web experiences enhanced by AI. Developers can run Gemini Pro in the cloud for natural language processing and other complex user journeys. Or, you explore the benefits of performing AI inferenceclient-side, with Gemini Nano in Chrome.
Build with usability and privacy in mind
As you embark on your AI development journey, we want you to keep in mind a few important considerations:
- Privacy: Prioritize user privacy and data security when implementing AI features, especially when handling sensitive user information. When it becomes available, opt for on-device AI solutions like Gemini Nano whenever possible to minimize data exposure.
- Seamless user experience: Ensure that AI features seamlessly integrate into your app’s overall user experience. AI should enhance the user experience, not disrupt it.
- Ethical considerations: AI technologies are developed and deployed in a way that benefits society while minimizing potential harm. By considering fairness, transparency, privacy, accountability, and societal impact, developers can play a vital role in creating a future where AI serves humanity’s best interests. Be mindful of the ethical implications of AI, such as potential biases in your AI models. Strive to create AI-powered features that are fair and inclusive.
AI on Android Spotlight Week is an opportunity to explore the latest in AI and its potential for Android app development. We encourage you to delve into the wealth of resources shared during the week and begin experimenting with AI in your own projects. The future of Android is rooted in AI and machine learning, and with the tools and knowledge shared during Android AI Week, developers are well-equipped to build the next generation of AI-powered apps.
What’s next
Come back to this blog post for updates; we’ll add links to blog and video content and more throughout the week. Follow Android Developers on X and Android Developers at LinkedIn, and remember to use the hashtag #AndroidAI to share your AI-powered Android creations, and join the vibrant community of developers pushing the boundaries of mobile AI.
