Generative AI- A brief about Challenges and Limitations Introduction: Generative AI , a subset of artificial intelligence that creates new content such as images, text, and audio, has seen remarkable advancements in recent years. Models like Generative Adversarial Networks (GANs) and transformers like GPT have pushed the boundaries of AI’s creative capabilities. However, despite its growing applications, generative AI faces numerous challenges and limitations that need to be addressed to maximize its potential responsibly and effectively. 1. Data Dependency and Quality Generative AI models require vast amounts of high-quality data to perform effectively. This data must be diverse and representative of the real-world environments in which the models will be deployed. However, acquiring such large datasets can be difficult, particularly for niche industries or applications. Additionally, the quality of the generated output depends heavily on the quality of the training data. Biased,...
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