Update URLs to redirects (#16048)

docs/en/guides/triton-inference-server.md

@@ -6,7 +6,7 @@ keywords: Triton Inference Server, YOLOv8, Ultralytics, NVIDIA, deep learning, A
 
 # Triton Inference Server with Ultralytics YOLOv8
 
-The [Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inference-server) (formerly known as TensorRT Inference Server) is an open-source software solution developed by NVIDIA. It provides a cloud inference solution optimized for NVIDIA GPUs. Triton simplifies the deployment of AI models at scale in production. Integrating Ultralytics YOLOv8 with Triton Inference Server allows you to deploy scalable, high-performance deep learning inference workloads. This guide provides steps to set up and test the integration.
+The [Triton Inference Server](https://developer.nvidia.com/triton-inference-server) (formerly known as TensorRT Inference Server) is an open-source software solution developed by NVIDIA. It provides a cloud inference solution optimized for NVIDIA GPUs. Triton simplifies the deployment of AI models at scale in production. Integrating Ultralytics YOLOv8 with Triton Inference Server allows you to deploy scalable, high-performance deep learning inference workloads. This guide provides steps to set up and test the integration.
 
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@@ -147,7 +147,7 @@ By following the above steps, you can deploy and run Ultralytics YOLOv8 models e
 
 ### How do I set up Ultralytics YOLOv8 with NVIDIA Triton Inference Server?
 
-Setting up [Ultralytics YOLOv8](https://docs.ultralytics.com/models/yolov8) with [NVIDIA Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inference-server) involves a few key steps:
+Setting up [Ultralytics YOLOv8](https://docs.ultralytics.com/models/yolov8) with [NVIDIA Triton Inference Server](https://developer.nvidia.com/triton-inference-server) involves a few key steps:
 
 1. **Export YOLOv8 to ONNX format**:
 
@@ -213,7 +213,7 @@ This setup can help you efficiently deploy YOLOv8 models at scale on Triton Infe
 
 ### What benefits does using Ultralytics YOLOv8 with NVIDIA Triton Inference Server offer?
 
-Integrating [Ultralytics YOLOv8](../models/yolov8.md) with [NVIDIA Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inference-server) provides several advantages:
+Integrating [Ultralytics YOLOv8](../models/yolov8.md) with [NVIDIA Triton Inference Server](https://developer.nvidia.com/triton-inference-server) provides several advantages:
 
 - **Scalable AI Inference**: Triton allows serving multiple models from a single server instance, supporting dynamic model loading and unloading, making it highly scalable for diverse AI workloads.
 - **High Performance**: Optimized for NVIDIA GPUs, Triton Inference Server ensures high-speed inference operations, perfect for real-time applications such as object detection.
@@ -223,7 +223,7 @@ For detailed instructions on setting up and running YOLOv8 with Triton, you can
 
 ### Why should I export my YOLOv8 model to ONNX format before using Triton Inference Server?
 
-Using ONNX (Open Neural Network Exchange) format for your [Ultralytics YOLOv8](../models/yolov8.md) model before deploying it on [NVIDIA Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inference-server) offers several key benefits:
+Using ONNX (Open Neural Network Exchange) format for your [Ultralytics YOLOv8](../models/yolov8.md) model before deploying it on [NVIDIA Triton Inference Server](https://developer.nvidia.com/triton-inference-server) offers several key benefits:
 
 - **Interoperability**: ONNX format supports transfer between different deep learning frameworks (such as PyTorch, TensorFlow), ensuring broader compatibility.
 - **Optimization**: Many deployment environments, including Triton, optimize for ONNX, enabling faster inference and better performance.
@@ -242,7 +242,7 @@ You can follow the steps in the [exporting guide](../modes/export.md) to complet
 
 ### Can I run inference using the Ultralytics YOLOv8 model on Triton Inference Server?
 
-Yes, you can run inference using the [Ultralytics YOLOv8](../models/yolov8.md) model on [NVIDIA Triton Inference Server](https://developer.nvidia.com/nvidia-triton-inference-server). Once your model is set up in the Triton Model Repository and the server is running, you can load and run inference on your model as follows:
+Yes, you can run inference using the [Ultralytics YOLOv8](../models/yolov8.md) model on [NVIDIA Triton Inference Server](https://developer.nvidia.com/triton-inference-server). Once your model is set up in the Triton Model Repository and the server is running, you can load and run inference on your model as follows:
 
 ```python
 from ultralytics import YOLO