Exam AI-900 topic 1 question 25 discussion

knowledge mining is not chatbot. it's Natural Language Processing.

Shouldn't the 1st one be Conversational AI? Altho bots can be built to explore the indexed data from Knowledge Mining.

The answer is correct. As for the first one, Knowledge mining is a powerful tool that can be used to create intelligent chatbots capable of answering complex questions, including those related to refunds and exchanges. By leveraging AI to understand and organize information, businesses can provide better customer service, improve efficiency, and gain valuable insights from their data.

nlp computer vision knowledgemining

My answer: NLP Computer vision NLP

Question 7 and 25 are same question but different answers Response should be : Conversational AI (for chatbot) Computer vision NLP

The last one should be Anomal detection

I think it should be NLP, CV, NLP

Knowledge Mining Data Extraction: Knowledge mining involves extracting useful information from large datasets. While it can be used to build a knowledge base for the chatbot, it is not the primary technology enabling the chatbot to interact with users. Supporting Role: Knowledge mining can support the chatbot by providing a rich database of information from which the chatbot can pull answers. However, the actual interaction and understanding of user queries are driven by NLP. In summary, while knowledge mining can enhance the chatbot’s database, NLP is the core technology

NLP-CV-NLP

knowledge mining.. Explore the newly indexed data via search, bots, existing business applications, and data visualizations.https://azure.microsoft.com/en-us/solutions/knowledge-mining/#tabxcf52f051b79e4b58b6bac20c2d430f7d

The answer should be: NLP-CV-NLP Here's the statement from NLP module: "In the following example, a chat bot uses natural language and provides options to a customer to best handle their query." Reference: https://learn.microsoft.com/en-us/training/modules/build-faq-chatbot-qna-maker-azure-bot-service/2-understand-question-answering?ns-enrollment-type=learningpath&ns-enrollment-id=learn.wwl.explore-natural-language-processing

Answer: NLM, CV, NLM I understand the chatbot question is debatable. A chatbot would use NLM to process and answer user questions about refunds and exchanges. It involves analyzing the text, finding the intent, and creating a response that is correct and related to the question. It would use Knowledge Mining to look through documents, FAQs, and other data sources to find answers to user questions. A possible solution for a chatbot to handle refunds and exchanges would combine both: • NLP to communicate with the user and comprehend their queries • Knowledge Mining to access the relevant information from the company’s rules and data sources to provide correct responses However, if I had to choose one, NLM would typically be the preferable option for several reasons that include: • Immediate Engagement • Customer Satisfaction • Instant Processing • Flexibility

It should be Natural Language Processing

Answer is not fully correct. It should be: 1. Generative AI. (Yes, i Know it is nog a given option, read below). 2. Computer Vision. 3. NLP. https://learn.microsoft.com/en-us/training/modules/get-started-ai-fundamentals/6-understand-generative-ai Generative AI applications take in natural language input, and return appropriate responses in a variety of formats including natural language, image, code, and audio. "Generative AI describes a category of capabilities within AI that create original content. People typically interact with generative AI that has been built into chat applications. Generative AI applications take in natural language input, and return appropriate responses in a variety of formats including natural language, image, code, and audio."

This is repeat Q of Question #7 and there the answer was Conversational AI for Chatbot though we had the options Knowledge mining and Conversational AI

Technically it can be counted as rule-based expert systems falling under knowledge mining, which is the old and legacy way of doing chatbots, but it still counts.