How can I inherit a flibjab in a jimjam bobsicle?

Asked on 2024-07-30

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It seems like your question is off-topic. However, I can provide information about the content presented by Apple at WWDC related to machine learning and AI. Here are some relevant sessions and their chapters:

  1. Deploy machine learning and AI models on-device with Core ML

    • Introduction
    • Integration
    • MLTensor
    • Models with state
    • Multifunction models
    • Performance tools

  2. Train your machine learning and AI models on Apple GPUs

    • Introduction
    • Training frameworks on Apple silicon
    • PyTorch improvements
    • ExecuTorch
    • JAX features

  3. Support real-time ML inference on the CPU

    • Introduction
    • Introducing BNNS Graph
    • Real-time processing
    • Adopting BNNS Graph
    • BNNS Graph in Swift

  4. Accelerate machine learning with Metal

    • Introduction
    • Transformer support
    • Fast Fourier transforms
    • MPS Graph viewer

If you have any specific questions about these sessions or need more detailed information, feel free to ask!

Deploy machine learning and AI models on-device with Core ML

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.

Train your machine learning and AI models on Apple GPUs

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.

Support real-time ML inference on the CPU

Support real-time ML inference on the CPU

Discover how you can use BNNSGraph to accelerate the execution of your machine learning model on the CPU. We will show you how to use BNNSGraph to compile and execute a machine learning model on the CPU and share how it provides real-time guarantees such as no runtime memory allocation and single-threaded running for audio or signal processing models.