Core ML에 대해서 자세히 설명해줘

Core ML is a powerful framework provided by Apple for deploying machine learning models on Apple devices. It is widely used across iOS, iPadOS, and macOS to enable AI-driven features in apps. Core ML automatically segments models across the CPU, GPU, and neural engine to maximize hardware utilization, ensuring efficient performance and a great user experience.

Key features of Core ML include:

1. Model Deployment: Core ML allows you to deploy machine learning models on Apple devices, enabling on-device inference which enhances privacy by keeping data local.

2. Performance Optimization: Core ML tools offer various optimization techniques, such as model compression and quantization, to improve the performance of models on Apple hardware.

3. Integration with Apple Ecosystem: Core ML integrates seamlessly with Apple's development environment, including Xcode, and supports a wide range of models, including those developed with PyTorch and other frameworks.

4. New Features: Recent updates have introduced new features like the ML tensor type for simplifying model integration, and enhanced performance reports for better optimization insights.

5. Support for Advanced Models: Core ML supports running advanced models like large language models and diffusion models, which can be imported and optimized for Apple devices.

For more detailed information, you can refer to the session Explore machine learning on Apple platforms (07:16) which covers running models on device and other advanced features of Core ML.