[doc] add Intel cooperation for biomedicine (#3108)

* [doc] add Intel cooperation for biomedicine

README-zh-Hans.md

@@ -196,6 +196,10 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
 
 - [Energon-AI](https://github.com/hpcaitech/EnergonAI) ：用相同的硬件推理加速50%
 
+<p id="OPT-Serving" align="center">
+<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20serving.png" width=600/>
+</p>
+
 - [OPT推理服务](https://colossalai.org/docs/advanced_tutorials/opt_service): 体验1750亿参数OPT在线推理服务
 
 <p id="BLOOM-Inference" align="center">
@@ -265,6 +269,12 @@ Colossal-AI 为您提供了一系列并行组件。我们的目标是让您的
 
 - [FastFold](https://github.com/hpcaitech/FastFold): 加速AlphaFold训练与推理、数据前处理、推理序列长度超过10000残基
 
+<p id="FastFold-Intel" align="center">
+<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/data%20preprocessing%20with%20Intel.jpg" width=600/>
+</p>
+
+- [FastFold with Intel](https://github.com/hpcaitech/FastFold): 3倍推理加速和39%成本节省
+
 <p id="xTrimoMultimer" align="center">
 <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/xTrimoMultimer_Table.jpg" width=800/>
 </p>

README.md

@@ -198,6 +198,10 @@ Please visit our [documentation](https://www.colossalai.org/) and [examples](htt
 
 - [Energon-AI](https://github.com/hpcaitech/EnergonAI): 50% inference acceleration on the same hardware
 
+<p id="OPT-Serving" align="center">
+<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/BLOOM%20serving.png" width=600/>
+</p>
+
 - [OPT Serving](https://colossalai.org/docs/advanced_tutorials/opt_service): Try 175-billion-parameter OPT online services
 
 <p id="BLOOM-Inference" align="center">
@@ -264,7 +268,13 @@ Acceleration of [AlphaFold Protein Structure](https://alphafold.ebi.ac.uk/)
 <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/FastFold.jpg" width=800/>
 </p>
 
-- [FastFold](https://github.com/hpcaitech/FastFold): accelerating training and inference on GPU Clusters, faster data processing, inference sequence containing more than 10000 residues.
+- [FastFold](https://github.com/hpcaitech/FastFold): Accelerating training and inference on GPU Clusters, faster data processing, inference sequence containing more than 10000 residues.
+
+<p id="FastFold-Intel" align="center">
+<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/data%20preprocessing%20with%20Intel.jpg" width=600/>
+</p>
+
+- [FastFold with Intel](https://github.com/hpcaitech/FastFold): 3x inference acceleration and 39% cost reduce.
 
 <p id="xTrimoMultimer" align="center">
 <img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/xTrimoMultimer_Table.jpg" width=800/>