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- Fix sample source path in build script:
  * openvino-fix-build-sample-path.patch
- Update to 2024.1.0
- More Generative AI coverage and framework integrations to
  minimize code changes.
  * Mixtral and URLNet models optimized for performance 
    improvements on Intel® Xeon® processors.
  * Stable Diffusion 1.5, ChatGLM3-6B, and Qwen-7B models 
    optimized for improved inference speed on Intel® Core™
    Ultra processors with integrated GPU.
  * Support for Falcon-7B-Instruct, a GenAI Large Language Model
    (LLM) ready-to-use chat/instruct model with superior
    performance metrics.
  * New Jupyter Notebooks added: YOLO V9, YOLO V8
    Oriented Bounding Boxes Detection (OOB), Stable Diffusion 
    in Keras, MobileCLIP, RMBG-v1.4 Background Removal, Magika, 
    TripoSR, AnimateAnyone, LLaVA-Next, and RAG system with 
    OpenVINO and LangChain.
- Broader Large Language Model (LLM) support and more model
  compression techniques.
  * LLM compilation time reduced through additional optimizations
    with compressed embedding. Improved 1st token performance of
    LLMs on 4th and 5th generations of Intel® Xeon® processors 
    with Intel® Advanced Matrix Extensions (Intel® AMX).
  * Better LLM compression and improved performance with oneDNN,
    INT4, and INT8 support for Intel® Arc™ GPUs.
  * Significant memory reduction for select smaller GenAI
    models on Intel® Core™ Ultra processors with integrated GPU.
- More portability and performance to run AI at the edge, 
  in the cloud, or locally.
  * The preview NPU plugin for Intel® Core™ Ultra processors
    is now available in the OpenVINO open-source GitHub 
    repository, in addition to the main OpenVINO package on PyPI.
  * The JavaScript API is now more easily accessible through
    the npm repository, enabling JavaScript developers’ seamless 
    access to the OpenVINO API.
  * FP16 inference on ARM processors now enabled for the 
    Convolutional Neural Network (CNN) by default.
- Support Change and Deprecation Notices
  * Using deprecated features and components is not advised. They
    are available to enable a smooth transition to new solutions 
    and will be discontinued in the future. To keep using 
    Discontinued features, you will have to revert to the last 
    LTS OpenVINO version supporting them.
  * For more details, refer to the OpenVINO Legacy Features 
    and Components page.
  * Discontinued in 2024.0:
    + Runtime components:
      - Intel® Gaussian & Neural Accelerator (Intel® GNA).
        Consider using the Neural Processing Unit (NPU) 
        for low-powered systems like Intel® Core™ Ultra or
        14th generation and beyond.
      - OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API 
        transition guide for reference).
      - All ONNX Frontend legacy API (known as 
        ONNX_IMPORTER_API)
      - 'PerfomanceMode.UNDEFINED' property as part of
         the OpenVINO Python API
    + Tools:
      - Deployment Manager. See installation and deployment
        guides for current distribution options.
      - Accuracy Checker.
      - Post-Training Optimization Tool (POT). Neural Network
        Compression Framework (NNCF) should be used instead.
      - A Git patch for NNCF integration with 
        huggingface/transformers. The recommended approach
        is to use huggingface/optimum-intel for applying 
        NNCF optimization on top of models from Hugging 
        Face.
      - Support for Apache MXNet, Caffe, and Kaldi model 
        formats. Conversion to ONNX may be used as 
        a solution.
  * Deprecated and to be removed in the future:
    + The OpenVINO™ Development Tools package (pip install
      openvino-dev) will be removed from installation options
      and distribution channels beginning with OpenVINO 2025.0.
    + Model Optimizer will be discontinued with OpenVINO 2025.0.
      Consider using the new conversion methods instead. For 
      more details, see the model conversion transition guide.
    + OpenVINO property Affinity API will be discontinued with 
      OpenVINO 2025.0. It will be replaced with CPU binding 
      configurations (ov::hint::enable_cpu_pinning).
    + OpenVINO Model Server components:
      - “auto shape” and “auto batch size” (reshaping a model
        in runtime) will be removed in the future. OpenVINO’s
        dynamic shape models are recommended instead.

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 A toolkit for optimizing and deploying AI inference  (fixed license tag from sr#1172510)

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