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[DOCS] fixes lts disclaimer master

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Karol Blaszczak 2023-11-27 14:58:10 +01:00 committed by GitHub
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4
docs/articles_en/documentation/openvino_legacy_features.md
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@ -60,7 +60,7 @@ offering.
| **Open Model ZOO**
| *New solution:* users are encouraged to use public model repositories
| *Old solution:* discontinuation planned for OpenVINO 2024.0
| *Old solution:* discontinuation planned for OpenVINO 2025.0
|
| Open Model ZOO provided a collection of models prepared for use with OpenVINO,
and a small set of tools enabling a level of automation for the process.
@ -85,7 +85,7 @@ offering.
| **Post-training Optimization Tool (POT)**
| *New solution:* NNCF extended in OpenVINO 2023.0
| *Old solution:* POT discontinuation planned for 2024
| *Old solution:* POT discontinuation planned for 2024.0
|
| Neural Network Compression Framework (NNCF) now offers the same functionality as POT,
apart from its original feature set. It is currently the default tool for performing

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docs/articles_en/learn_openvino/openvino_samples/cpp_sample_automatic_speech_recognition.md
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@ -11,10 +11,11 @@
.. note::
This sample is being deprecated and will no longer be maintained after
OpenVINO 2023.2 (LTS). The main reason for it is the outdated state of
the sample and its extensive usage of GNA, which is not going to be
supported by OpenVINO beyond 2023.2.
This sample is now deprecated and will be removed with OpenVINO 2024.0.
The sample was mainly designed to demonstrate the features of the GNA plugin
and the use of models produced by the Kaldi framework. OpenVINO support for
these components is now deprecated and will be discontinued, making the sample
redundant.
This sample demonstrates how to execute an Asynchronous Inference of acoustic model based on Kaldi\* neural networks and speech feature vectors.

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docs/articles_en/learn_openvino/openvino_samples/python_sample_automatic_speech_recognition.md
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@ -11,10 +11,11 @@
.. note::
This sample is being deprecated and will no longer be maintained after
OpenVINO 2023.2 (LTS). The main reason for it is the outdated state of
the sample and its extensive usage of GNA, which is not going to be
supported by OpenVINO beyond 2023.2.
This sample is now deprecated and will be removed with OpenVINO 2024.0.
The sample was mainly designed to demonstrate the features of the GNA plugin
and the use of models produced by the Kaldi framework. OpenVINO support for
these components is now deprecated and will be discontinued, making the sample
redundant.
This sample demonstrates how to do a Synchronous Inference of acoustic model based on Kaldi\* neural models and speech feature vectors.

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docs/install_guides/pypi-openvino-dev.md
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@ -3,7 +3,7 @@
<!--- The note below is intended for master branch only for pre-release purpose. Remove it for official releases. --->
> **NOTE**: This version is pre-release software and has not undergone full release validation or qualification. No support is offered on pre-release software and APIs/behavior are subject to change. It should NOT be incorporated into any production software/solution and instead should be used only for early testing and integration while awaiting a final release version of this software.
> **NOTE**: OpenVINO™ Development Tools package has been deprecated and will be discontinued with 2024.0 release. To learn more, refer to the [OpenVINO Legacy Features and Components page](https://docs.openvino.ai/2023.2/openvino_legacy_features.html).
> **NOTE**: OpenVINO™ Development Tools package has been deprecated and will be discontinued with 2025.0 release. To learn more, refer to the [OpenVINO Legacy Features and Components page](https://docs.openvino.ai/2023.2/openvino_legacy_features.html).
Intel® Distribution of OpenVINO™ toolkit is an open-source toolkit for optimizing and deploying AI inference. It can be used to develop applications and solutions based on deep learning tasks, such as: emulation of human vision, automatic speech recognition, natural language processing, recommendation systems, etc. It provides high-performance and rich deployment options, from edge to cloud.