Why is ChatGPT helpless in the challenge of counting from 1 to 1 million?

DNVN - Many people have challenged ChatGPT with a seemingly simple task: counting from 1 to 1 million. The model always refused or stopped halfway. Why can't an artificial intelligence that can analyze complex text, even write essays, complete such a seemingly easy task?

Many people who first come into contact with ChatGPT often try simple requests to verify the capabilities of this artificial intelligence. One of the familiar requests is “count from 1 to 1 million”. The answer is often a refusal, or ChatGPT only lists a short paragraph and then stops. In fact, this is not because the model cannot count or lacks logical capabilities, but comes from technical limitations, design orientation and the nature of the language model. It is these factors that make a seemingly simple task impossible.

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ChatGPT is built on top of large language models, which work by predicting the next word or character based on a given text string. All data generated by the system is divided into small units called tokens. A token can be a word, a part of a word, or a special character. For each chat session, the model is only capable of processing and generating a certain number of tokens.

With the latest versions, this number can be up to more than 200,000 tokens, a huge step forward compared to before. However, if the requirement to count from 1 to 1 million, the amount of data that needs to be generated will still far exceed this limit. Just printing one million integers requires about 2-3 million tokens, many times the maximum capacity of any model at the present time. This is a clear technical barrier and cannot be overcome under current conditions.

Even assuming that the system has no capacity limit, counting to 1 million is not practical. Reading or displaying the entire series of numbers would take a very long time without any useful information. In text form, you would have to scroll through hundreds of thousands of lines. In voice form, listening to a machine read each number for days is completely unreasonable. The design philosophy of ChatGPT is to optimize the user experience and provide knowledge value, not to perform repetitive actions that traditional computers can do much better. Instead of counting directly, ChatGPT often suggests writing a short code in Python or another programming language. The computer can run this code in a few millionths of a second to list the entire series of numbers, allowing them to be stored, searched, and processed more efficiently.

Another important aspect is the nature of language models. Humans can count numbers sequentially using logic and memory, with enough patience, without any problems. In contrast, ChatGPT does not “count” in the mathematical sense, but only predicts text patterns that are likely to appear next. When asked to count from 1 to 10, the system easily generates the correct sequence because it is a familiar pattern in the training data. But when scaled to millions of elements, the model will have difficulty because it is not designed to perform such a long sequential process. Its goal is natural communication, answering questions, analyzing and creating content, not replacing a mere computer loop.

It is also important to note that the system is built to serve millions of users at once. If a single person were to force ChatGPT to generate a huge amount of text, it would use up server resources needlessly and affect the experience of others. Therefore, at the core of the design, there are mechanisms to block or limit requests that do not provide a clear benefit. This is why ChatGPT can reject requests like counting to 1 million, listing all prime numbers under a very large number, or generating thousands of pages of text consisting of just one repeated word.

The “unable to count to 1 million” story leads us to a more important conclusion: not every task is suitable for language models. ChatGPT is good at natural language processing, interpretation, analysis, and text generation, but it is not suitable for purely mechanical tasks. If we think of ChatGPT as a general-purpose machine that can do everything, we will be disappointed by such limitations. But if we understand its characteristics and combine it with other tools such as programming languages, databases, or computational software, users will take full advantage of the power that the system brings.

Therefore, when someone challenged ChatGPT to count from 1 to 1 million, the result was a clear demonstration of the difference between linguistic AI and a traditional computer. Artificial intelligence was not created to replace monotonous repetitive operations, but to support humans in processing complex information, providing knowledge and suggesting ideas. This seemingly simple limit, if viewed from a scientific perspective, is a reminder of the right approach: using the right tool for the right purpose. ChatGPT may not count to 1 million, but it can analyze why the number 1 million has important meaning in economics , science or culture. And that is the core value of artificial intelligence technology in modern life.

Bao Ngoc (t/h)

Source: https://doanhnghiepvn.vn/cong-nghe/vi-sao-chatgpt-bat-luc-truoc-thu-thach-dem-tu-1-den-1-trieu/20250919024144154