What is the Difference Between Generative AI and Conversational AI?

Basically, the difference between generative AI (GAI) and conversational AI (CAI) is that generative AI produces original content and creations when prompted, while conversational AI specialises in holding authentic and useful two-way interactions with humans by understanding and responding in text or speech. 

Generative AI and conversational AI are both types of artificial intelligence and both use Natural Language Processing, however they are used for different purposes and have distinct characteristics.  

Purpose of Generative AI 

The main function of generative AI is to create entirely new content, such as text, images, or even music. What it produces is not directly dependent on user input but uses human prompts to spark a new creation. Generative AI is also used for producing programming code. 

Purpose of Conversational AI 

Conversational AI is designed to communicate with people using natural language. It uses Natural Language Understanding to understand what a person is saying, be it through text or voice, and then generate life-like and intelligible responses. CAI can also pick up on a person’s intent (what they are really saying or wanting to do), recognise entities (useful data like dates and names), and read a person’s state, for example, whether they are in a vulnerable situation. 

Use Cases 

Where is Generative AI used? 

GAI is versatile and can be used successfully in chatbots, content generation, creative writing, and producing art and writing music scores. Examples include text generation like with ChatGPT and image generation as used by Midjourney. For instance, the worlds of design and architecture are being challenged by sophisticated GAI capabilities, as are spheres like creative writing and music composition. 

Where is Conversational AI used? 

CAI interacts with humans in text or voice conversations which makes them perfect for chatbots, virtual assistants, customer engagement and customer service, education, and any other area where human-like interaction is useful.  It automates many of the mundane and repetitive tasks that human employees find tedious and time-consuming. 

How are they Trained? 

What are Generative AI models trained on? 

GAI models are often trained on varied and extremely large datasets, mainly drawn from the Internet, they are founded on Large Language Models, and built using deep learning and neural network technology. (See: What is a Large Language Model). They learn to generate content by predicting the next most likely word in a sequence.  

What are Conversational AI models trained on? 

Conversational AI models are trained on conversational datasets that include real-life dialogues and interactions. These are often specific to the industry that the AI chatbot is being used in (learn more about Custom Language Models). They learn to generate responses that make sense in the context of a conversation. (See: How Does Conversational AI Work?)

Comparison of Generative AI and Conversational AI Chatbots
Feature Generative AI Chatbots Conversational AI Chatbots
Primary Function Generates new creative text formats, like poems, code, scripts, musical pieces, email, letters, etc. Simulates human conversation by understanding and responding to user queries in a natural and engaging way.
Focus Creativity and originality Realism and human-likeness
Input Text, code, or other data Natural language text or voice
Output New creative text, image, music Human-like responses to user queries
Training Data Large datasets e.g. Internet Large datasets of human conversations
Applications Content creation, research, coding, images... and more.... Customer service, virtual assistants, and chatbots
Examples ChatGPT, LaMDA Amazon Lex, IBM Watson Assistant, Google Dialogflow

Where does Ethical AI Fit In? 

Generative AI Ethics 

GAI is known to hallucinate between 15% and 20% of the time, which makes it too inaccurate for certain enterprise functions. It can also sometimes generate biased or inappropriate content, so the designers of the GAI system need to be extra vigilant in training and use continuous improvement to weed out unethical responses. Other examples of grey ethics are deepfakes where people are ‘made’ to say and do things that they did not actually say or do. Or in the case of music where AI technology is being used to mimic popular singers or their song writing styles. 

Conversational AI Ethics 

Conversational AI must be designed to handle user data and conversations with privacy and security in mind. Also, conversational AI chatbots that are used by businesses have to be strictly controlled to stay within compliance rules and regulations. 


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