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Tackling the major roadblocks of text-based GenAI

In recent years, the field of text-based generative artificial intelligence (AI) has witnessed remarkable advancements, revolutionizing natural language processing and generating human-like textual content. These AI models, such as GPT-3, have demonstrated unprecedented capabilities in generating coherent stories, answering questions, and even simulating human conversation.

However, within this realm of immense promise, lie substantial challenges and obstacles that demand prudent navigation. As text-based generative AI achieves unprecedented capabilities, it simultaneously encounters complex roadblocks that necessitate careful consideration. These challenges encompass a range of intricate issues that span from accuracy and coherence to ethical considerations and contextual understanding.

This report aims to explore and dissect the major roadblocks encountered in the domain of text-based generative AI and present effective strategies to overcome them.

 

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In recent years, the field of text-based generative artificial intelligence (AI) has witnessed remarkable advancements, revolutionizing natural language processing and generating human-like textual content. These AI models, such as GPT-3, have demonstrated unprecedented capabilities in generating coherent stories, answering questions, and even simulating human conversation.

However, within this realm of immense promise, lie substantial challenges and obstacles that demand prudent navigation. As text-based generative AI achieves unprecedented capabilities, it simultaneously encounters complex roadblocks that necessitate careful consideration. These challenges encompass a range of intricate issues that span from accuracy and coherence to ethical considerations and contextual understanding.

This report aims to explore and dissect the major roadblocks encountered in the domain of text-based generative AI and present effective strategies to overcome them.

 

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