Discover 75 articles on AI in mobile performance
Showing 15 of 75 articles (Page 4 of 4)
Sandhya Mohan from Google just dropped the biggest Gemini in Android Studio update since launch. If you're still manually writing commit messages and test scenarios, this changes everything.
What if you could ditch Xcode's sluggish editor and use VSCode/Cursor for iOS development? Turns out, you can build a surprisingly functional setup.
DoorDash handles 2 billion orders annually, and every ETA prediction matters. Their old tree-based models couldn't keep up with the complexity.
Taj Darra just announced that Google is opening Gemini Nano to all Android developers. On-device AI just became accessible for production-ready mobile apps.
Przemyslaw Weglik from Software Mansion shows how to run real-time AI models directly on mobile devices using React Native. No server calls, no latency, just pure on-device inference.
Jakub Chmura from Software Mansion shows how to run AI models directly on iOS devices without a single API call. No cloud dependency, no latency, just native performance.
Uber's mobile testing was broken. Engineers spent 30-40% of their time maintaining test scripts that broke with every UI change. So they built an AI that tests apps like a human would.
Very Good Ventures took the stage at Google Cloud Next 2024 to show how Flutter and Gemini are changing the game development playbook. Literally.
Dave Burke, VP of Engineering at Google, just dropped the playbook for integrating Gemini AI into Android apps. If you've been waiting for the right moment to add generative AI to your mobile stack, this is it.
Dave Burke from Google just dropped the blueprint for running foundation models directly on your Android device. No cloud required, no network dependency, just pure on-device AI.
Snap Research just proved that Vision Transformers can run as fast as MobileNet on actual mobile devices. Yes, really.
Ishan Khanna from Tinder shares a hard-earned lesson: that shiny third-party SDK could be a ticking time bomb for your app. Here's the framework his team uses to avoid disaster.
Pinterest just shipped a feature that 60% of their top beauty searches were literally asking for. Yanis Markin walks through how they combined ML with inclusive design to solve it.
Cesario Putera from Blibli.com shows how Google's ML Kit brings powerful face detection to Android apps with surprisingly little code. No PhD required.
Meta has been quietly building the foundation for interfaces that understand speech, vision, touch, and text simultaneously. The future of mobile isn't single-mode anymore.