CoreML

Core ML is a key framework for deploying machine learning models on Apple devices, as highlighted in several sessions at WWDC 2024. It allows developers to run a wide array of AI models, including large language models and diffusion models, on iOS, iPadOS, and macOS. Core ML optimizes hardware utilization by automatically segmenting models across the CPU, GPU, and neural engine, ensuring efficient execution.

Some of the new features and improvements in Core ML include:

• ML Tensor Type: Designed to simplify the computational glue code for stitching models together.
• State Management: Enhancements for managing key-value caches, particularly useful for large language models.
• Performance Reports: Updated to provide more insights into the cost of each operation within a model.
• Model Compression Techniques: New techniques to optimize models for Apple hardware, balancing storage size, latency, and accuracy.

For more detailed information, you can refer to the following sessions:

• Explore machine learning on Apple platforms (07:16)
• Deploy machine learning and AI models on-device with Core ML (01:07)

These sessions provide insights into the latest advancements in Core ML and how they can be leveraged to enhance app performance and user experience.