The Story of a Bill: How Well Can AI Models Handle Real-World Math
Large Language Models (LLMs) have proven effective in tasks like natural language processing, sentiment analysis, data extraction, and answering questions. According to ChatGPT, complex mathematical operations for it include advanced techniques such as calculus, matrix operations, differential equations, optimization, and probability, often used for solving real-world problems in fields like engineering, physics, and economics. And complex data analysis involves multivariate analysis, statistical modeling, time series analysis, machine learning, and big data handling, used for discovering patterns, making predictions, and drawing insights from large datasets. Recently, we've explored multiple LLMs’ ability to handle basic mathematical and analytical operations, including additions, subtractions, multiplication, division and percentage calculations and financial data analysis. While LLMs can manage basic arithmetic, While LLMs can manage basic arithmetic, we tested their ability to solve more complex tasks using a restaurant bill, and tried to convert the bill into a table, split the total amount, and calculate each person's percentage share.
