CBNITS

  A form of conversational AI known as generative AI chatbots utilizes deep learning and natural language processing (NLP) techniques to produce human-like text responses instantly during interactions. These chatbots engage in text-based conversations, comprehend user input, and generate relevant responses within context. Key aspects of Generative AI include enhanced natural language understanding (NLU), improved text generation, contextual comprehension, minimized biases, extensive training on large datasets, increased capabilities, and growing concerns regarding ethical usage, among others. The adoption of generative AI by numerous organizations is notable, with approximately one-third of surveyed entities incorporating it into at least one operational function. This translates to about 60 percent of AI-adopting organizations integrating generative AI into their systems. Future developments in generative chatbots are anticipated to encompass enhanced multitasking, heightened emotio

  Since OpenAI released ChatGPT, there have been great leaps of progress in the field of generative AI. Generative AI is a type of artificial intelligence focused on the ability of computers to use models to create content like images, text, code, and synthetic data. Generative AI applications are built on top of large language models (LLMs) and foundation models. Chatbots using LLMs can handle a wide range of tasks, including customer support, information retrieval, language translation, content generation, and more. They offer a sophisticated conversational experience that approaches human-like interaction, although they still have limitations and may occasionally produce incorrect or nonsensical responses.   CBNITS creating & co-piloting Generative AI chatbots using large language models for finance, healthcare and security industries Because many large language models are trained on general data, they can only answer general questions. They are better at interpreting human lan