Merge pull request #816 from JohnSnowLabs/chore/add_new_blog_links

Chore/add new blog links

README.md

@@ -110,8 +110,8 @@ You can check out the following langtest articles:
 | [**LangTest: Unveiling & Fixing Biases with End-to-End NLP Pipelines**](https://www.johnsnowlabs.com/langtest-unveiling-fixing-biases-with-end-to-end-nlp-pipelines/) | The end-to-end language pipeline in LangTest empowers NLP practitioners to tackle biases in language models with a comprehensive, data-driven, and iterative approach. |
 | [**Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest**](https://medium.com/john-snow-labs/beyond-accuracy-robustness-testing-of-named-entity-recognition-models-with-langtest-fb046ace7eb9) | While accuracy is undoubtedly crucial, robustness testing takes natural language processing (NLP) models evaluation to the next level by ensuring that models can perform reliably and consistently across a wide array of real-world conditions. |
 | [**Elevate Your NLP Models with Automated Data Augmentation for Enhanced Performance**](https://medium.com/john-snow-labs/elevate-your-nlp-models-with-automated-data-augmentation-for-enhanced-performance-71aa7812c699) | In this article, we discuss how automated data augmentation may supercharge your NLP models and improve their performance and how we do that using  LangTest. |
-| [**Mitigating Gender-Occupational Stereotypes in AI: Evaluating Models with the Wino Bias Test through Langtest Library**](To Be Published Soon) | In this article, we discuss how we can test the "Wino Bias” using LangTest. It specifically refers to testing biases arising from gender-occupational stereotypes. |
-| [**Automating Responsible AI: Integrating Hugging Face and LangTest for More Robust Models**](To Be Published Soon) | In this article, we have explored the integration between Hugging Face, your go-to source for state-of-the-art NLP models and datasets, and LangTest, your NLP pipeline’s secret weapon for testing and optimization. |
+| [**Mitigating Gender-Occupational Stereotypes in AI: Evaluating Models with the Wino Bias Test through Langtest Library**](https://www.johnsnowlabs.com/mitigating-gender-occupational-stereotypes-in-ai-evaluating-language-models-with-the-wino-bias-test-through-the-langtest-library/) | In this article, we discuss how we can test the "Wino Bias” using LangTest. It specifically refers to testing biases arising from gender-occupational stereotypes. |
+| [**Automating Responsible AI: Integrating Hugging Face and LangTest for More Robust Models**](https://www.johnsnowlabs.com/automating-responsible-ai-integrating-hugging-face-and-langtest-for-more-robust-models/) | In this article, we have explored the integration between Hugging Face, your go-to source for state-of-the-art NLP models and datasets, and LangTest, your NLP pipeline’s secret weapon for testing and optimization. |
 
 > **Note**
 > To checkout all blogs, head over to [Blogs](https://www.johnsnowlabs.com/responsible-ai-blog/)