16 articles on AI for Android performance
Showing 16 of 16 articles (Page 1 of 1)
Callstack has open-sourced agent-device, a lightweight CLI tool that enables AI coding agents like Claude Code and Codex to automate interactions with iOS and Android apps. The tool provides lifecycle managemen...
Details how Grindr automated memory leak debugging to reduce diagnosis time from hours to minutes using AI techniques.
Instacart's Caper team shares their four-phase strategy for migrating their smart cart Android app from Fragments and XML layouts to Jetpack Compose. AI coding assistants accelerated the refactoring by 5-7x, sa...
How Automated Prompt Optimization (APO) on Vertex AI enables developers to achieve fine-tuning-quality results for on-device Gemini Nano models, with 5-8% accuracy gains across classification and translation ta...
Discusses improvements to AI/ML capabilities on Android platform for mobile development.
Guide on developing applications for Android XR platform and AI glasses devices.
In 2025, AI became our star driver. After years of building the infrastructure — Mercury for test and release management, Helios for VM orchestration
WhatsApp/Messenger moved key models on-device; reduced model load & inference time and improved ANR metrics. (Engineering at Meta)
Covers AI-powered development tools and Gemini integration in Android Studio for improved developer experience.
DoorDash uses deep learning to nail ETA predictions with precision.
Covers integration of on-device AI models for Android mobile app development.
Discusses foundational AI capabilities and frameworks for Android mobile development.
Uber’s AI-powered DragonCrawl makes mobile testing sharper and more efficient.
Discusses engineering practices and quality assurance processes for Android development at Tinder.
Covers implementing face detection functionality in Android applications using Google's ML Kit library.
Meta explores new ways to mix voice, touch, and more in app design.