Link fix 2 (#1523)

* Fix broken links

Signed-off-by: Chris Abraham <[email protected]>

* fix link

Signed-off-by: Chris Abraham <[email protected]>

---------

Signed-off-by: Chris Abraham <[email protected]>

Author: cjyabraham

_posts/2022-5-12-ambient-clinical-intelligence-generating-medical-reports-with-pytorch.md

@@ -271,4 +271,4 @@ Finally, efficient deployment to the cloud is about more than just computing the
 
 ## Conclusion
 
-Academia has long recognized that we are "standing on the shoulders of giants." As Artificial Intelligence is maturing from a scientific discipline into technology, the same spirit of collaboration that originally fueled its scientific foundation has carried over into the world of software engineering. Open-source enthusiasts join technology companies worldwide to build open software ecosystems that allow for new angles at solving some of the most pressing challenges of modern society. In this article, we've taken a look at Nuance's [Dragon Ambient eXperience](http://www.nuance.com/ambient), an AI-powered, voice-enabled solution that automatically documents patient care, reducing healthcare providers' administrative burdens. Nuance DAX improves the patient-provider experience, reduces physician burnout, and improves financial outcomes. It brings back trust, joy, and humanity to the delivery of healthcare. Fairseq and PyTorch have proven to be an incredible platform for powering this AI technology, and in turn, Nuance has contributed back some of its innovations in this space. For further reading, we invite you to take a look at our recent [ACL publication](https://www.aclweb.org/anthology/2020.nlpmc-1.4/) and the [Nuance "What's Next" blog](https://whatsnext.nuance.com/rd/using-deep-learning-to-generate-medical-reports/).
+Academia has long recognized that we are "standing on the shoulders of giants." As Artificial Intelligence is maturing from a scientific discipline into technology, the same spirit of collaboration that originally fueled its scientific foundation has carried over into the world of software engineering. Open-source enthusiasts join technology companies worldwide to build open software ecosystems that allow for new angles at solving some of the most pressing challenges of modern society. In this article, we've taken a look at Nuance's [Dragon Ambient eXperience](http://www.nuance.com/ambient), an AI-powered, voice-enabled solution that automatically documents patient care, reducing healthcare providers' administrative burdens. Nuance DAX improves the patient-provider experience, reduces physician burnout, and improves financial outcomes. It brings back trust, joy, and humanity to the delivery of healthcare. Fairseq and PyTorch have proven to be an incredible platform for powering this AI technology, and in turn, Nuance has contributed back some of its innovations in this space. For further reading, we invite you to take a look at our recent [ACL publication](https://www.aclweb.org/anthology/2020.nlpmc-1.4/) and the Nuance "What's Next" blog.

_posts/2023-11-16-accelerating-generative-ai.md

@@ -263,7 +263,7 @@ Methods for pruning are varied, from completely unstructured, wherein weights ar
 ![dense tensor output that can leverage highly performant, 2:4 GPU kernels](/assets/images/accelerating-generative-ai/sparse_image.png){:style="width:100%;display: block;max-width:600px; margin-left:auto; margin-right:auto;"}
 
 
-From [developer.nvidia.com/blog/exploiting-ampere-structured-sparsity-with-cusparselt](developer.nvidia.com/blog/exploiting-ampere-structured-sparsity-with-cusparselt)
+From [developer.nvidia.com/blog/exploiting-ampere-structured-sparsity-with-cusparselt](https://developer.nvidia.com/blog/exploiting-ampere-structured-sparsity-with-cusparselt)
 
 In order to use this sparse storage format and the associated fast kernels we need to prune our weights such that they adhere to the constraints for the format. We pick the two smallest weights to prune in a 1 by 4 region, measuring the performance vs accuracy tradeoff. It is easy to change a weight from its default PyTorch (“strided”) layout to this new, semi-structured sparse layout. To implement `apply_sparse(model)` we only require 32 lines of Python code:
 

_sass/fonts.scss

@@ -59,7 +59,7 @@
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   font-style: normal;
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+       url($baseurl + "/assets/fonts/FreightSans/freight-sans-book.woff") format("woff");
 }
 
 @font-face {