Ever since the launch of large language models such as ChatGPT, scientists, engineers and public are trying to find various ways to automate complicated computing tasks with natural language processing. Researchers from Brown University have proposed an interesting framework which enables to use natural language processing (NLP) to help with scientific computing tasks. They called the framework MyCrunchGPT, which is a chatbot that can assist you with scientific machine learning (SciML) problems.

SciML can be challenging and time-consuming, as it involves many steps such as pre-processing, problem formulation, code generation, post-processing and analysis. Moreover, SciML may not be accessible to everyone, especially those who are not familiar with coding or physics.

This is where MyCrunchGPT comes in. MyCrunchGPT is a chatbot that uses ChatGPT to communicate with the user and guide them through the SciML workflow. ChatGPT is based on GPT-3, which is one of the most advanced NLP models that can generate natural and coherent texts based on user prompts. CrunchGPT leverages ChatGPT to understand the user's queries, provide relevant information, generate code snippets, plot graphs, and produce summary reports.

To demonstrate the capabilities of CrunchGPT, the authors of the paper present two examples: (1) design and optimization of 2D NACA airfoils, and (2) solving prototype fluid mechanics problems using physics-informed neural networks (PINNs). In both cases, CrunchGPT can help the user with various tasks such as defining the problem, choosing the parameters, running the simulations, visualizing the results, and validating the accuracy. The user can interact with CrunchGPT using natural language or simple commands, and get instant feedback and guidance.

The authors also provide a web-based user interface for CrunchGPT, which allows the user to choose from different options and see the results in real time. The user can also request a comprehensive summary report that contains all the information and outputs generated by CrunchGPT. The authors claim that CrunchGPT can be a useful tool for researchers, engineers, students, and educators who want to use SciML for their problems.

CrunchGPT is an innovative and exciting framework that shows the potential of using NLP for scientific computing. By using ChatGPT as a conductor, CrunchGPT can orchestrate the entire SciML workflow and make it easier and more accessible for everyone. If you want to learn more about CrunchGPT, you can read the full paper here.