We can see the significant improvement of AI in recent years. In previous years, although we saw some applications of AI, they were used to process input and map it to predefined output. These days, AI has become generative, meaning we no longer need to program chatbots with specific outputs. Instead, they can generate text based on the questions we ask. Chatbots are developed using Large Language Models (LLMs) trained with diverse datasets, allowing them to perform natural language processing efficiently. The use of machine learning and deep learning made chatbots efficient. We have chatbots like GPT-4, Google’s chatbot Gemini, Perplexity AI, etc.
Recent Advancements:

• As discussed above, chatbots are able to understand natural language and process it to give results. Additionally, we can converse in regional languages as well.
• We have multimodal AI, which means this model can process text, images, and audio.
• We have generative AI that can generate text, images, or audio without the need for pre-programmed outputs, e.g., Microsoft Bing, ChatGPT.
• Advancements in the medical field are evident as we have chatbots that can make diagnoses, such as CodyAI.

Advantages and Disadvantages:
     The advantages of these chatbots are vast. With extensive information storage and natural language processing, they can guide us like teachers. In business applications and the healthcare industry, they provide 24/7 assistance, are easy to use, and reliable. However, there are also disadvantages. Chatbots have access to sensitive content, leading to security concerns. Some prompts can mislead AI and result in incorrect answers. AI should be used to handle routine and exhausting tasks, while creative and innovative work should always be done by humans. Over-reliance on chatbots for problem-solving can lead to a lack of skills, potentially making the idea that AI will replace humans a reality.