Hello, I have been interacting with ChatGPT for quite some time and have noticed that errors often arise due to the lack of self-verification before delivering a response. I have developed a method that minimizes errors, and I would like to propose integrating it into the model’s algorithms.
The essence of the method:
Before generating a response, ChatGPT checks its output against the key parameters of the query. For example, if a user asks for “new movies of 2024 that haven’t been mentioned in previous lists,” the model verifies:
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Are the movies from 2024?
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Have these movies already been included in earlier lists?
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Do they meet the criteria for “new” (i.e., not repeated)?
This would significantly reduce errors, especially in lists, dates, repeated information, and logical inconsistencies.
Real-Life Example and Results:
I have applied a similar system of self-verification in my own life to minimize mistakes and errors. By using a method of continuous self-checking, I have dramatically reduced the number of mistakes I make in both personal and professional tasks. For example, when managing projects, I often pause to verify if my actions align with the requirements before proceeding. This approach has led to significantly fewer errors and more accurate outcomes.
I believe that implementing this approach within ChatGPT could similarly improve accuracy and reliability.
I would be happy to discuss this idea in more detail and provide further examples. I hope the OpenAI team will consider this suggestion!
Best regards,
VittaPR