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[DOCS] prerelease notes 0329 (#16584)

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@ -15,11 +15,40 @@ a general changelog and the schedule for all versions for the current year.
* Introduced to allow early testing and get early feedback from the community.
.. dropdown:: OpenVINO Toolkit 2023.0.0.dev20230217
.. dropdown:: OpenVINO Toolkit 2023.0.0.dev20230229
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:animate: fade-in-slide-down
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* Added remote tensor support (accepting tensor located in graph memory) in C API 2.0
* Introduced model caching on GPU. Model Caching which reduces First Inference Latency (FIL) is
extended to work as a single method on both CPU and GPU plug-ins.
* Added the post-training Accuracy-Aware Quantization mechanism for OpenVINO IR. By using this mechanism
the user can define the accuracy drop criteria and NNCF will consider it during the quantization.
* CPU plugin migrated to OneDNN 3.1.
* AUTO supports fall-back to CPU device in case of run-time failure of networks on accelerator devices.
* AUTO supports the option to disable CPU as the initial acceleration device to speed up first-inference latency.
* Implementing a parameter enabling network inference independently of IR precision. The default mode will be FP16
with FP32 as an option to increase accuracy. General hints (performance vs accuracy) to be provided.
* Adding support for new model use cases or optimizing the existing support (better accuracy or performance).
* Performance on dGPU optimized with Intel oneDNN v3.1, especially for transformer models.
* Dynamic shapes supported on iGPU and dGPU for Transformer(NLP) models. Not all dynamic models are supported but model coverage will be expanded in future releases.
* Performance improvement for Transformer models for NLP pipelines on CPU.
* Models:
* Enabled MLPerf RNN-T model.
* Enabled Detectron2 MaskRCNN.
* Enabled OpenSeeFace models.
* Enabled Clip model.
* Optimized WeNet model.
.. dropdown:: OpenVINO Toolkit 2023.0.0.dev20230217
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OpenVINO™ repository tag: `2023.0.0.dev20230217 <https://github.com/openvinotoolkit/openvino/releases/tag/2023.0.0.dev20230217>`__
* Enabled PaddlePaddle Framework 2.4