Conversational AI simulates human conversations through natural language processing (NLP) and other related techniques such as transformers. Conversational AI can interpret user input and generate appropriate responses based on its understanding of the user’s intent. The responses can be in the form of text, voice, or other modalities, depending on the application, such as virtual assistants, chatbots, and voice assistants, among others. This is most likely what most people are familiar with regarding conversational AI thanks to the swift popularity of OpenAI’s ChatGPT. Conversational AI systems can be trained on large amounts of data to improve their ability to understand and respond to user input. They can also use context to generate more personalized responses that are tailored to the user’s specific needs and preferences. Conversational AI is a rapidly evolving field, and researchers and developers are constantly exploring new ways to improve the technology’s capabilities and expand its applications. Conversational AI has the potential to dramatically change how organizations interact with data, systems, and workflows, making it possible to create more personalized and intuitive experiences with deeper insights and value. With further advancements in NLP, machine learning (ML), and other related fields, conversational AI is poised to become even more integral to organizations in the years to come. Generative AI, on the other hand, uses algorithms to generate new content such as images, text, and music. Unlike traditional ML algorithms, designed to classify or predict existing data, generative AI models are trained to generate new data that resembles a specific dataset. Generative AI uses special algorithms to learn from existing examples and then generates new content that looks and sounds similar to what it learned. For example, generative AI can be used to create new artwork that is inspired by existing artwork. It can also generate realistic images of things that don’t exist, or it can write stories or articles that sound like they were written by a person.