Adds links to new blog. (#221)

README.md

@@ -20,6 +20,9 @@ establishing a new SOTA in the LM category.
 
 
 # News
+
+* [2020/05/19] [ZeRO-2 & DeepSpeed: Shattering Barriers of Deep Learning Speed & Scale](https://www.microsoft.com/en-us/research/blog/zero-2-deepspeed-shattering-barriers-of-deep-learning-speed-scale/)
+<span style="color:dodgerblue">**[_NEW_]**</span>
 * [2020/05/19] [An Order-of-Magnitude Larger and Faster Training with ZeRO-2](https://www.deepspeed.ai/news/2020/05/19/zero-stage2.html)
 <span style="color:dodgerblue">**[_NEW_]**</span>
 * [2020/05/19] [The Fastest and Most Efficient BERT Training through Optimized Transformer Kernels](https://www.deepspeed.ai/news/2020/05/19/bert-record.html)

docs/_posts/2020-05-19-bert-record.md

@@ -17,6 +17,6 @@ DeepSpeed achieves the fastest BERT training record: 44 minutes on 1,024
 NVIDIA V100 GPUs**, compared with the best published result of 67 minutes on
 the same number and generation of GPUs.
 
-For a technical overview, see our [blog post](linklink).
+For a technical overview, see our [blog post](https://www.microsoft.com/en-us/research/blog/zero-2-deepspeed-shattering-barriers-of-deep-learning-speed-scale/).
 
 **Code and tutorials are coming soon!**

docs/_posts/2020-05-19-press-release.md

+---
+layout: single
+title: "ZeRO-2 & DeepSpeed: Shattering Barriers of Deep Learning Speed & Scale"
+excerpt: ""
+link: https://www.microsoft.com/en-us/research/blog/zero-2-deepspeed-shattering-barriers-of-deep-learning-speed-scale/
+categories: news
+new_post: true
+date: 2020-05-19 02:00:00
+---

docs/_posts/2020-05-19-zero-stage2.md

@@ -17,7 +17,7 @@ learning training by an order of magnitude. More concretely, ZeRO-2 allows
 training models as large as 170 billion parameters up to 10x faster compared
 to state of the art.
 
-For more information on ZeRO-2 overview, see our [blog post](linklink).
+For more information on ZeRO-2, see our [blog post](https://www.microsoft.com/en-us/research/blog/zero-2-deepspeed-shattering-barriers-of-deep-learning-speed-scale/).
 
 For more information on how to use ZeRO-2, see an example of training GPT family of models in this [tutorial](/tutorials/megatron/).