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README.md

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-Our project, Polyglot, aims to bridge the linguistic gap in NLP and supplement the field's current shortcomings by creating efficient foundation models for low-resource languages.
+Polyglot is an initiative to close the linguistic divide in NLP by developing efficient and accessible foundation models for low-resource languages.
 
-In recent years, generative AI has seen remarkable advancements, with foundation models emerging as the cornerstone of much of the research and development in the field. However, the prevailing deep learning paradigm demands vast resources in terms of data and computation. This data-intensive approach has inadvertently deepened the divide between high-resource and low-resource languages. High-resource languages benefit from the bulk of development efforts and readily available resources, while low-resource languages face significant challenges in achieving comparable performance and autonomy.
+While recent breakthroughs in generative AI have been driven by large-scale foundation models, these advances have largely benefited high-resource languages, leaving many underrepresented languages behind. The current deep learning paradigm—heavily reliant on massive datasets and computing power—has unintentionally widened this gap, making it harder for speakers of low-resource languages to access and shape AI technologies that reflect their linguistic and cultural identities.
 
-To foster a more equitable, sustainable, and open ecosystem for AI research and development, we aim to create tools and resources to support the development of foundation models for low-resource languages. This includes developing models, datasets, and open-source code to empower underrepresented linguistic communities.
+Polyglot addresses this imbalance by creating tools, models, and datasets that support open, sustainable, and inclusive AI development. We aim to empower researchers and communities working with low-resource languages through high-quality open-source resources, enabling them to build and fine-tune language models tailored to their needs.
 
 ## Recent Publications 📚