Why ChatGPT isn't Good at Math: A Study by Akash Mittal

Have you ever asked ChatGPT, an AI chatbot, to help you solve a math problem? If yes, you might have noticed that ChatGPT isn't good at math. Let me share an interesting story with you that will explain why this is so.

A friend of mine was struggling with a math problem, so I recommended ChatGPT to him. He messaged ChatGPT his problem, but to our surprise, the answer provided by the chatbot was incorrect. We tried a few more questions, and again, the answers weren't right. This made us wonder why ChatGPT isn't good at math, a subject that is considered one of the fundamental strengths of AI.

After some research, I found that ChatGPT uses the GPT-3 model, which is primarily designed for language-related tasks. Although the GPT-3 model can perform simple arithmetic and solve mathematical problems, it isn't trained specifically for that task. This results in ChatGPT sometimes providing wrong answers to math problems, as it lacks the deep mathematical knowledge that a human mathematician or specialized AI model would have.

Real-life examples have also proven that some companies that have tried to incorporate math into their AI systems face similar challenges. One such company is Xnor.ai, a leading AI startup that focuses on machine learning and computer vision. They have developed an AI chip that can accurately recognize an object without being connected to a database or the internet. However, when they tried to incorporate math into their model, the accuracy level decreased significantly.

Another example is Google's AlphaGo, an AI program that can play the ancient Chinese board game, Go. AlphaGo defeated the world champion in 2016, but it also struggled with more complex math problems.

In conclusion, although AI has made significant advancements in recent years, it still lacks the deep mathematical knowledge that humans possess. ChatGPT, Xnor.ai, and AlphaGo are some examples of companies that have faced challenges in this area. Nevertheless, this shouldn't discourage us from further exploring the potential of AI. With more research and development, we can create AI models that are not only good at language-related tasks but also adept at solving complex math problems.