ChatGPT has already demonstrated mind-blowing capabilities in natural language understanding and processing. Its power can be greatly enhanced further to perform more complex tasks using prompt engineering, domain-specific fine-tuning, retrieval-augmented generation (RAG), and collaborative agents.
Can ChatGPT understand chemistry? A paper from Nature Machine Intelligence demonstrates that domain-specific fine-tuning of GPT-3 can perform classification and regression tasks for predicting molecular properties, such as solid-solution formation and Henry’s coefficient. It can even design new molecules based on instructions and specified properties. Traditionally, people have built complex ML or AI-based QSAR models for these tasks. If this new approach works, it will fundamentally change the approach in chemical and material sciences, and perhaps in all branches of science.