Updates to homepage and credits page

_posts/2025-04-23-pytorch-2-7.md

@@ -5,7 +5,7 @@ title: "PyTorch 2.7 Release"
 
 We are excited to announce the release of PyTorch® 2.7 ([release notes](https://github.com/pytorch/pytorch/releases/tag/v2.7.0))! This release features: 
 
-* support for the NVIDIA Blackwell GPU architecture and pre-built wheels for CUDA 12.8 across Linux x86 and arm64 architectures. 
+* support for the [NVIDIA Blackwell GPU architecture](https://www.nvidia.com/en-us/data-center/technologies/blackwell-architecture/) and pre-built wheels for [CUDA 12.8](https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html) across Linux x86 and arm64 architectures. 
 * *torch.compile* support for Torch Function Modes which enables users to override any *torch.** operation  to implement custom user-defined behavior. 
 * Mega Cache which allows users to have end-to-end portable caching for torch; 
 * new features for FlexAttention - LLM first token processing, LLM throughput mode optimization and Flex Attention for Inference.

credits.html

@@ -21,9 +21,9 @@ <h1>PyTorch Cloud<br />&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Credit Program<
       <div class="col-md-10 body-side-text">
         <div class="row">
           <div class="col-md">
-            <p class="lead">We believe providing public, self-service, and automated access to Cloud Infrastructure is crucial for every project to incubate, grow, and succeed.
+            <p class="lead">We believe providing public, self-service, and automated access to cloud infrastructure is essential for every project's incubation, growth, and success.
               <br /><br />
-              That’s why PyTorch has created the Cloud Credits program, focussed on the mutual success of projects and participating companies. To date, supporters like AWS have donated cloud credits to showcase direct support of our incubating and graduated projects. In fact, many organizations sponsor PyTorch projects for their business to succeed.
+              To support this, PyTorch has established a program that enables organizations to contribute either cloud credits or financial donations directly towards maintaining and expanding our Continuous Integration (CI) infrastructure and other foundation-hosted project infrastructure. Contributions from organizations like AWS have already provided cloud credits, demonstrating a clear commitment to the success and sustainability of the PyTorch' Foundation's hosted projects. Many organizations continue to sponsor PyTorch projects, recognizing that supporting foundational infrastructure contributes directly to their own business growth and success.
             </p>
           </div>
           <div class="col-md">

index.html

@@ -31,11 +31,11 @@ <h3>Blog</h3>
         </p>
       </div>
       <div class="col-md">
-        <h3>PyTorch 2.6</h3>
+        <h3>PyTorch 2.7</h3>
         <p>
-          Featuring Python 3.13 support for torch.compile, several AOTInductor enhancements, FP16 support on X86 CPUs, and more.
+          Includes support for NVIDIA Blackwell GPUs, CUDA 12.8 wheels for Linux x86 and arm64, Torch Function Modes in <code>torch.compile</code>, Mega Cache for portable compilation artifacts, and new FlexAttention features for LLM inference.
         <p>
-          <a href="/blog/pytorch2-6/">Learn more</a>
+          <a href="/blog/pytorch-2-7/">Learn more</a>
         </p>
       </div>
       <div class="col-md">