A PhD Student’s Perspective on Research in NLP in the Era of Very Large Language Models As our IFAN project was recommended as one of the promising research direction, I will also recommend in return to read the recent paper to answer the question: "So what now in NLP research if ChatGPT is out?" Spoiler: the world has not ended and we still have plenty work to do! https://arxiv.org/abs/2305.12544 From my research work and what I also want to explore, my top list of research directions: 1. Misinformation fight. There is still zero online working automated fake news and propaganda detection systems. However, the risk of misinformation spread is increasing. 2. Multilingualism. A usual reminder, that there is more languages rather then English. Like at least 7k more. 3. Explainability and Interpretabilty. Do we trust models' decisions? Still absolutely far away from 100%. We can help to integrate these models into decisions making process only if their behavior will be transparent. And now think about if we can even explain every NLP task. The methods are absolutely different. 4. Less resources. Less memory to store models and fine-tune them. Less also data to learn! Do we need indeed all these training samples? Or we just need diverse enough data? 5. Human-NLP models interaction. What we can admit is that ChatGPT was the first NLP model used not only by specialists but by everyone. Because it is more or less pleasant and safe to use it. If the model cannot answer some input, it provides anyway nicely written answer. The wrapper is also extremely important. How we need to cover those models that user will be comfortable to work with it? What about children if we want to adjust them for education even from early ages? Be brave, be creative, be inspired✨