  The generative pre-trained transformer (GPT)-based chatbot software ChatGPT
possesses excellent natural language processing capabilities but is inadequate
for solving arithmetic problems, especially multiplication. Its GPT structure
uses a computational graph for multiplication, which has limited accuracy
beyond simple multiplication operations. We developed a graph-based
multiplication algorithm that emulated human-like numerical operations by
incorporating a 10k operator, where k represents the maximum power to base 10
of the larger of two input numbers. Our proposed algorithm attained 100%
accuracy for 1,000,000 large number multiplication tasks, effectively solving
the multiplication challenge of GPT-based and other large language models. Our
work highlights the importance of blending simple human insights into the
design of artificial intelligence algorithms. Keywords: Graph-based
multiplication; ChatGPT; Multiplication problem
