What Does It Mean to Know? Building a Tibetan AI Called མཁྱེན། Khyen

1. 1Explore the limitations of current NLP models for low-resource languages
2. 2Research alternative approaches to building AI models for languages with limited online data
3. 3Develop a custom dataset for the Tibetan language to train AI models
4. 4Experiment with transfer learning and fine-tuning techniques for Tibetan language AI
5. 5Evaluate the performance of Tibetan AI models using relevant metrics and benchmarks

NLP engineers and researchers working with low-resource languages can benefit from this approach, as it highlights the challenges of developing AI models for languages with limited online presence

💡 Developing AI models for low-resource languages like Tibetan requires innovative approaches to data collection and model training

🤖 Building a Tibetan AI requires rethinking AI capabilities due to limited online presence #NLP #LowResourceLanguages