Natural Language Processing (NLP) is a transformative technology, but it has its limitations. Understanding these intricacies is crucial to determine the future of the technology.
- Biases in Language Models
Language models have an inherent bias. AI models are trained on large datasets which have biases. This can result in unfair or discriminatory outcomes, impacting areas where NLP will be implemented. Recognizing and reducing these biases will be a concern in NLP research and development.
- Data Dependency
NLP models require vast amounts of text data for training, which can be a barrier. Especially for less-resourced languages or niche areas, it could be very challenging.
- Handling Multiple Languages and Dialects:
The world is very diverse in its linguistic landscape. There are more than thousands of languages and dialects. Building NLP models that can understand and process so much is difficult. There are many multilingual models, but they still face language and dialect challenges.
