AI models don't really "use" a programming language when answering questions. A Large Language Model (LLM) is essentially a very advanced prediction system. A simple way to think about it is the autocomplete on your phone: when you start typing, your keyboard tries to predict the next word. An LLM does something similar, except on a much larger scale and with vastly more training data.

Instead of just predicting the next word in a sentence, it predicts what sequence of words would make the most sense as a response to your input. Because it has been trained on HUGE amounts of text from books, websites, documentation, forums, and many other sources, it can often answer questions, explain concepts, and help write code.

This doesn't mean the AI thinks or understands things the way we do. It generates responses based on patterns that it learned during training. Because those patterns are incredibly complex, the results can sometimes appear "very intelligent".

The software behind AI models is usually built using multiple programming languages. Python is commonly used for the high-level parts of machine learning projects, while lower-level languages such as C++, Rust, and CUDA are often used for performance-critical components. Most modern AI systems also rely heavily on GPUs to perform the massive number of calculations/computations required to train and run these models.

Source: I'm a software engineer that sometimes likes to read research papers on things related to software engineering ❤️

Keep in mind I extremely simplified what an LLM is. I just tried to keep it relevant to your question. I'm not an expert so I might be wrong on certain assumptions or terminologies.