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The field of AI is evolving every day. With more advancements and easy integration, it is difficult to understand the difference between different technologies. Two such technologies that play an important role in our day-to-day lives are generative AI and conversational AI. Both of these technologies are subfields of artificial intelligence and have many things in common. However, they are not to be confused with each other or the same, as we will break down their differences here. In this blog, we shall understand the differences between Generative AI vs Conversational AI.  

What is Generative AI vs Conversational AI 

Both generative AI and conversational AI use natural language processing and Large language models to perform their functions. However, their purpose vary from each other. Generative AI creates new content based on your prompt, like text, code, images, music, etc. On the other hand, Conversational AI focuses on human-to-computer interactions. It engages with humans in human-like interactions.  

The Basics of Generative AI vs Conversational AI 

The main goal of conversational AI is to improve humans’ interaction with computers through natural language. It can read and understand the language humans use. It can also pick important details from the interactions and understand the sentiments. This type of AI is used in chatbots, AI virtual assistants, etc.  In contrast, generative AI has the goal of creating new content. It mimics human intelligence and uses a large amount of data for training. It can generate a wide range of content like code, music, text, images, synthetic data, etc.  

Main Differences Between Generative AI vs Conversational AI 

To use both the technology in the right ways and leverage it for business growth, one must know them well. When it comes to techniques, conversational AI uses natural language processing, machine learning, and dialogue management, while generative AI uses deep learning, generative adversarial networks, variational autoencoders, and transformers. The purpose of conversational AI is to simulate human conversations, while that of generative AI is to create new content. Key applications of generative AI include text, image, music, and code generation, while those of conversational AI are chatbots, virtual assistants, and customer service. Conversational AI focuses on understanding and responding to human language. In contrast, generative AI focuses on creating novel content from learned patterns. When it comes to training data, conversational AI uses conversations and domain-specific dialogues, differing from generative AI, which uses diverse content for training. The output of generative AI is either text, image, sound, code, or synthetic data, while conversational AI’s output is either text or voice response to humans. These are the major differences between generative AI and conversational AI.  

Are Generative AI and Conversational AI Mutually Exclusive? 

In real-world applications, both generative AI and conversational AI are often combined. In such AI systems, they co-exist and offer double advantages. One of the best examples is ChatGPT, which is technically a conversational AI, but it can also generate content with its generative features.  

Conclusion 

Both generative AI and conversational AI are a part of artificial intelligence technology. Using NLP, machine learning, and neural networks, they mimic human intelligence to respond to conversations or generate content. A trustworthy AI development company like AnavClouds Analytics.ai can help business owners tailor AI technology to suit their requirements. Give your organization an AI-powered boost with us. Book a demo today! 


Source: https://www.anavcloudsanalytics.ai/blog/generative-ai-vs-conversational-ai/