What are the latest tools to help developers create ML models?
Generated on 2/7/2025
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At WWDC 2024, Apple introduced several new tools and enhancements to help developers create machine learning models. Here are some of the highlights:
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Create ML Enhancements: The Create ML app has been updated with new templates and components. Developers can now use the app to customize machine learning models for various tasks, such as object detection and time series forecasting. The app also includes a new object tracking template for Apple Vision Pro, allowing developers to train reference objects to anchor spatial experiences on visionOS. What’s new in Create ML (00:00:51).
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Core ML Tools: Apple has introduced new model compression techniques and optimizations in Core ML tools. These enhancements allow developers to optimize models for Apple hardware, balancing storage size, latency, and accuracy. The tools also support transformer-specific operations and multifunction models. Explore machine learning on Apple platforms (07:16).
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Integration with Apple Silicon: Developers can leverage Apple's hardware by preparing and optimizing their models for Apple silicon using Core ML tools. This includes using familiar frameworks like PyTorch powered by Metal for training or fine-tuning models on Mac GPUs. Bring your machine learning and AI models to Apple silicon (02:47).
These tools and enhancements are designed to make it easier for developers to build, optimize, and deploy machine learning models across Apple's platforms.
Bring your machine learning and AI models to Apple silicon
Learn how to optimize your machine learning and AI models to leverage the power of Apple silicon. Review model conversion workflows to prepare your models for on-device deployment. Understand model compression techniques that are compatible with Apple silicon, and at what stages in your model deployment workflow you can apply them. We’ll also explore the tradeoffs between storage size, latency, power usage and accuracy.
Train your machine learning and AI models on Apple GPUs
Learn how to train your models on Apple Silicon with Metal for PyTorch, JAX and TensorFlow. Take advantage of new attention operations and quantization support for improved transformer model performance on your devices.
What’s new in Create ML
Explore updates to Create ML, including interactive data source previews and a new template for building object tracking models for visionOS apps. We’ll also cover important framework improvements, including new time-series forecasting and classification APIs.
Explore machine learning on Apple platforms
Get started with an overview of machine learning frameworks on Apple platforms. Whether you’re implementing your first ML model, or an ML expert, we’ll offer guidance to help you select the right framework for your app’s needs.
Deploy machine learning and AI models on-device with Core ML
Learn new ways to optimize speed and memory performance when you convert and run machine learning and AI models through Core ML. We’ll cover new options for model representations, performance insights, execution, and model stitching which can be used together to create compelling and private on-device experiences.
Platforms State of the Union
Discover the newest advancements on Apple platforms.