Fix Xeon reference per its trademark (#803)

Signed-off-by: Malini Bhandaru <malini.bhandaru@intel.com>

AudioQnA/README.md

@@ -4,7 +4,7 @@ AudioQnA is an example that demonstrates the integration of Generative AI (GenAI
 
 ## Deploy AudioQnA Service
 
-The AudioQnA service can be deployed on either Intel Gaudi2 or Intel XEON Scalable Processor.
+The AudioQnA service can be deployed on either Intel Gaudi2 or Intel Xeon Scalable Processor.
 
 ### Deploy AudioQnA on Gaudi
 

ChatQnA/README.md

@@ -95,7 +95,7 @@ flowchart LR
 
 ```
 
-This ChatQnA use case performs 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 ChatQnA use case performs 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.
 
 In the below, we provide a table that describes for each microservice component in the ChatQnA architecture, the default configuration of the open source project, hardware, port, and endpoint.
 
@@ -114,7 +114,7 @@ In the below, we provide a table that describes for each microservice component
 
 ## Deploy ChatQnA Service
 
-The ChatQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The ChatQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 
 Two types of ChatQnA pipeline are supported now: `ChatQnA with/without Rerank`. And the `ChatQnA without Rerank` pipeline (including Embedding, Retrieval, and LLM) is offered for Xeon customers who can not run rerank service on HPU yet require high performance and accuracy.
 

DocSum/README.md

@@ -10,7 +10,7 @@ The architecture for document summarization will be illustrated/described below:
 
 ## Deploy Document Summarization Service
 
-The Document Summarization service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The Document Summarization service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 Based on whether you want to use Docker or Kubernetes, follow the instructions below.
 
 Currently we support two ways of deploying Document Summarization services with docker compose:

FaqGen/README.md

@@ -6,7 +6,7 @@ Our FAQ Generation Application leverages the power of large language models (LLM
 
 ## Deploy FAQ Generation Service
 
-The FAQ Generation service can be deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The FAQ Generation service can be deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 
 ### Deploy FAQ Generation on Gaudi
 

SearchQnA/README.md

@@ -22,7 +22,7 @@ The workflow falls into the following architecture:
 
 ## Deploy SearchQnA Service
 
-The SearchQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The SearchQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 
 Currently we support two ways of deploying SearchQnA services with docker compose:
 

Translation/README.md

@@ -6,11 +6,11 @@ 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 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.
 
 ## Deploy Translation Service
 
-The Translation service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The Translation service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 
 ### Deploy Translation on Gaudi
 

VideoQnA/README.md

@@ -85,14 +85,14 @@ flowchart LR
     DP <-.->|d|VDB
 ```
 
-- This project implements a Retrieval-Augmented Generation (RAG) workflow using LangChain, Intel VDMS VectorDB, and Text Generation Inference, optimized for Intel XEON Scalable Processors.
+- This project implements a Retrieval-Augmented Generation (RAG) workflow using LangChain, Intel VDMS VectorDB, and Text Generation Inference, optimized for Intel Xeon Scalable Processors.
 - Video Processing: Videos are converted into feature vectors using mean aggregation and stored in the VDMS vector store.
 - Query Handling: When a user submits a query, the system performs a similarity search in the vector store to retrieve the best-matching videos.
 - Contextual Inference: The retrieved videos are then sent to the Large Vision Model (LVM) for inference, providing supplemental context for the query.
 
 ## Deploy VideoQnA Service
 
-The VideoQnA service can be effortlessly deployed on Intel XEON Scalable Processors.
+The VideoQnA service can be effortlessly deployed on Intel Xeon Scalable Processors.
 
 ### Required Models
 

VisualQnA/README.md

@@ -30,7 +30,7 @@ You can choose other llava-next models, such as `llava-hf/llava-v1.6-vicuna-13b-
 
 ## Deploy VisualQnA Service
 
-The VisualQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel XEON Scalable Processors.
+The VisualQnA service can be effortlessly deployed on either Intel Gaudi2 or Intel Xeon Scalable Processors.
 
 Currently we support deploying VisualQnA services with docker compose.