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Overestimation of capabilities
Generative AI can only generate output based on given training material. If AI is not properly trained, the resulting output may be inadequate, leading to incorrect call lists decisions and wasted resources. For example, AI technology may not be able to recognize recent world events if the training material is older than recent events. As a result, you may not be able to obtain accurate factual insights.
unexpected output
Most generative AI technologies require a human to provide prompts or input. That means you have to ask the right questions to get the results you want. The output of AI is difficult to control and can sometimes produce unexpected or inaccurate results.
Overall, generative AI is a powerful technology that can streamline business operations. However, it is important to remember that generative AI has limitations and must be used cautiously and cautiously. With the right knowledge and strategy, companies can leverage the power of generative AI to gain an advantage in their respective markets.
Challenges of Generative AI
Although the field of generative AI has made great strides, there are still some challenges and complexities in introducing AI into business and everyday life.
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Limitations of ChatGPT(Limitations of ChatGPT, a generative AI technology)
data quality
AI models rely heavily on data accuracy and quality. If your data training set is inaccurate or insufficient, your results may be poor.
