●PLAY — Google Play's target API level 36 requirement took effect yesterday, August 31. From today, new apps and updates must target Android 16●VISIBILITY — Apps still on API 35 stay listed but disappear for users on newer Android versions. No error is raised; new installs simply fade, which makes the change easy to miss●EXTENSION — If you missed the deadline, an extension through November 1, 2026 can be requested in Play Console — best filed alongside a concrete migration plan●APPLE — On the Apple side, the event lands September 9 and iOS 27 is reported to ship September 14. Testing generated apps on iOS 27 hardware before release week is time well spent●EXPO — Expo released expo-paste-input on August 28, a native module that brings image, GIF, and sticker paste to React Native TextInput●EAS — EAS Observe reached general availability on August 20, putting crash and performance monitoring on the same EAS platform as builds and updates●PLAY — Google Play's target API level 36 requirement took effect yesterday, August 31. From today, new apps and updates must target Android 16●VISIBILITY — Apps still on API 35 stay listed but disappear for users on newer Android versions. No error is raised; new installs simply fade, which makes the change easy to miss●EXTENSION — If you missed the deadline, an extension through November 1, 2026 can be requested in Play Console — best filed alongside a concrete migration plan●APPLE — On the Apple side, the event lands September 9 and iOS 27 is reported to ship September 14. Testing generated apps on iOS 27 hardware before release week is time well spent●EXPO — Expo released expo-paste-input on August 28, a native module that brings image, GIF, and sticker paste to React Native TextInput●EAS — EAS Observe reached general availability on August 20, putting crash and performance monitoring on the same EAS platform as builds and updates

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machine-learning

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rork-max² core-ml² rork¹ optimization¹ neural-engine¹ ios¹ on-device-ai¹ vision-framework¹ app-development¹

⬡ Rork Dev/2026-04-24Advanced

Optimizing Machine Learning in Rork Max Apps — Core ML Integration, Per-Device Tuning, Quantization, Size Reduction

A complete playbook for integrating Core ML into SwiftUI apps generated by Rork Max: model conversion, quantization, Neural Engine targeting, battery management, and per-device tuning — written at the implementation level, not the marketing one.

◉ Rork AI/2026-03-28Advanced

Rork × Core ML Custom Model Development × On-Device AI

Notes from training a model in Create ML, shipping it inside a Rork Max app with Core ML, and deciding per request whether inference runs on device or in the cloud — with measured routing, quantization, Vision and Natural Language integration, and OTA model swaps.