Here are some of the common errors that ChatGPT can make:
-
Lack of Common Sense: ChatGPT was trained on a large dataset of text, but it may not have enough information about the real world to make inferences about common sense knowledge.
-
Repetition and Lack of Variation: ChatGPT may generate repetitive answers or lack variation in its responses, especially when generating text for a prompt that it has seen many times before.
-
Bias in the Training Data: The training data used to train ChatGPT may contain biases and inaccuracies, which the model can then propagate in its responses.
-
Overgeneralization: ChatGPT can sometimes overgeneralize and provide responses that are not relevant or appropriate for the specific context or prompt.
-
Sensitivity to Input Errors: ChatGPT may generate incorrect responses or fail to provide a response altogether if the input is poorly formatted, misspelled, or ambiguous.
-
Lack of Contextual Awareness: ChatGPT may struggle to understand the context of a conversation and provide irrelevant or nonsensical responses.
It's important to keep these limitations in mind when using ChatGPT and to thoroughly evaluate the model's outputs before deploying it in real-world applications.
Join the ChatGPT Course today and start building advanced chatbots and virtual assistants!
