Update README.md

README.md

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   * [https://blog.google/](https://blog.google/)  
   * [https://cloud.google.com/blog/](https://cloud.google.com/blog/)  
   * [https://deepmind.google/discover/blog/](https://deepmind.google/discover/blog/)  
-  * [https://developers.google.com/learn?category=aiandmachinelearning](https://developers.google.com/learn?category=aiandmachinelearning)   
+  * [https://developers.google.com/learn?category=aiandmachinelearning](https://developers.google.com/learn?category=aiandmachinelearning)
+  * [https://research.google/blog/](https://research.google/blog/)   
 * **Notable GitHub Repositories**:  
   * [https://github.com/google/jax](https://github.com/google/jax) is a Python library for high-performance numerical computing and machine learning  
   * [https://github.com/huggingface/Google-Cloud-Containers](https://github.com/huggingface/Google-Cloud-Containers) facilitate the training and deployment of Hugging Face models on Google Cloud  
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   * [https://github.com/google/flax](https://github.com/google/flax) is a neural network library for JAX that is designed for flexibility  
   * [https://github.com/kubernetes-sigs/lws](https://github.com/kubernetes-sigs/lws) facilitates Kubernetes deployment patterns for AI/ML inference workloads, especially multi-host inference workloads  
   * [https://github.com/GoogleCloudPlatform/ai-on-gke](https://github.com/GoogleCloudPlatform/ai-on-gke) is a collection of AI examples, best-practices, and prebuilt solutions  
-* **Google AI Research Papers**: [https://research.google/](https://research.google/) 
+* **Google Research Papers**: [https://research.google/](https://research.google/) 
 
 ## On-device ML using [Google AI Edge](http://ai.google.dev/edge)