Update README.md for Multiplatforms (#834)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: yinghu5

MultimodalQnA/README.md

@@ -91,7 +91,9 @@ flowchart LR
 
 ```
 
-This MultimodalQnA use case performs Multimodal-RAG using LangChain, Redis VectorDB and Text Generation Inference on Intel Gaudi2 or Intel Xeon Scalable Processors. The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Visit [Habana AI products](https://habana.ai/products) for more details.
+This MultimodalQnA use case performs Multimodal-RAG using LangChain, Redis VectorDB and Text Generation Inference on [Intel Gaudi2](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html) and [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon.html), and we invite contributions from other hardware vendors to expand the example.
+
+The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Visit [Habana AI products](https://habana.ai/products) for more details.
 
 In the below, we provide a table that describes for each microservice component in the MultimodalQnA architecture, the default configuration of the open source project, hardware, port, and endpoint.
 

Translation/README.md

@@ -6,7 +6,7 @@ Translation architecture shows below:
 
 ![architecture](./assets/img/translation_architecture.png)
 
-This Translation use case performs Language Translation Inference on Intel Gaudi2 or Intel Xeon Scalable Processors. The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Visit [Habana AI products](https://habana.ai/products/) for more details.
+This Translation use case performs Language Translation Inference across multiple platforms. Currently, we provide the example for [Intel Gaudi2](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html) and [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon.html), and we invite contributions from other hardware vendors to expand OPEA ecosystem.
 
 ## Deploy Translation Service
 

VisualQnA/README.md

@@ -13,7 +13,9 @@ General architecture of VQA shows below:
 
 ![VQA](./assets/img/vqa.png)
 
-This example guides you through how to deploy a [LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT) (Open Large Multimodal Models) model on Intel Gaudi2 to do visual question and answering task. The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Please visit [Habana AI products](https://habana.ai/products/) for more details.
+This example guides you through how to deploy a [LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT) (Open Large Multimodal Models) model [Intel Gaudi2](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html) and [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon.html). We invite contributions from other hardware vendors to expand OPEA ecosystem.
+
+The Intel Gaudi2 accelerator supports both training and inference for deep learning models in particular for LLMs. Visit [Habana AI products](https://habana.ai/products) for more details.
 
 ![llava screenshot](./assets/img/llava_screenshot1.png)
 ![llava-screenshot](./assets/img/llava_screenshot2.png)