WWDC24: Train your machine learning and AI models on Apple GPUs | Apple
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. Discuss this video on the Apple Developer Forums: https://developer.apple.com/forums/to... 00:00 - Introduction 01:36 - Training frameworks on Apple silicon 04:16 - PyTorch improvements 11:26 - ExecuTorch 13:19 - JAX features More Apple Developer resources: Video sessions: https://apple.co/VideoSessions Documentation: https://apple.co/DeveloperDocs Forums: https://apple.co/DeveloperForums App: https://apple.co/DeveloperApp
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WWDC24: Meet Swift Testing | Apple
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WWDC26: Run local agentic AI on the Mac using MLX | Apple
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WWDC22: Accelerate machine learning with Metal | Apple
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WWDC24: Bring your machine learning and AI models to Apple silicon | Apple
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WWDC26: Bringing Cyberpunk 2077 to Mac | Apple
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WWDC26: Integrate on-device AI models into your app using Core AI | Apple
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WWDC26: Explore numerical computing in Swift with MLX | Apple
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WWDC24: SwiftUI essentials | Apple
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WWDC24: Say hello to the next generation of CarPlay design system | Apple
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WWDC25: Combine Metal 4 machine learning and graphics | Apple
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WWDC25: Explore large language models on Apple silicon with MLX | Apple
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WWDC26: Create UI prototypes using agents in Xcode | Apple
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WWDC25: Discover machine learning & AI frameworks on Apple platforms | Apple
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WWDC25: Deep dive into the Foundation Models framework | Apple
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WWDC24: Explore machine learning on Apple platforms | Apple
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SwiftUI foundations: Build great apps with SwiftUI | Meet with Apple
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WWDC25: Get started with MLX for Apple silicon | Apple
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WWDC24: Go small with Embedded Swift | Apple
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WWDC24: A Swift Tour: Explore Swift’s features and design | Apple
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