limitation of Generative ai

limitation of Generative ai 
Generative AI, while impressive, has its limitations. It can produce content that appears realistic but may lack true comprehension or context understanding. This can result in the generation of incorrect or biased information. Moreover, ethical concerns regarding the misuse of generative AI for generating fake news, deep fakes, or other deceptive content are significant challenges. 

Incapable of learning independently :
Generative models are trained on a fixed set of data and do not learn new information on their own. They do rely on external inputs for additional context but do not modify their underlying knowledge base. You may be able to provide them with domain specific knowledge and industry context, but these technologies will require specific training to be adapted to each business environment and company needs.

Unable to replace human traits :
 Like creativity, emotional intelligence or proactive learning. These tools are completely unable to sense human thoughts, feelings, or to grasp fresh ideas. At the moment, they are not even close to fully replacing a human being in a task where human traits are needed. There are configuration options for tools like ChatGPT, so that the output is more creative (0 to 1 “temperature” in system prompts) but this tends to lead to a higher degree of inaccuracy and the system sometimes comes up randomly with totally fake information.

Difficulty to cite sources :
These models do not store information in a way that allows citation. Meaning, it will not be easy to substantiate your work when some of it comes from tools like ChatGPT. This requires professionals to do extra work in documenting where key data is gathered or unverified information may be a problem down the road. There are some articles here and there), guiding users on how to get these technologies to cite sources but it does not always work and the tool may provide fake citations or just miss key sources of the main information.

Lack of certainty : 
GenAI cannot reassess or be certain about it responses, even if it seems confident. They operate based on wording probabilities, leading grammatically correct responses but potentially inaccurate outputs. Professionals should never take the validity of information for granted.

Hard-to-identify artificial content :
 As generative technologies advance, distinguishing between human and AI-fueled content becomes harder and harder. Tools designed to detect AI-generated content are not close to bulletproof while the line between artificial and genuine continues to blur. This may seem like a benefit to many professionals but in reality this is what leaves room for fake news, wrong insights and similar problems in society.

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