AI-900: Unlocking the Power of Conversational AI: Practical Applications and Benefits

Discover the diverse applications of conversational AI in enhancing customer experiences and streamlining operations. Explore scenarios such as telephone answering services, chatbots for self-service, voice menus, and FAQ document creation, and learn how conversational AI can drive efficiency, improve customer satisfaction, and provide valuable insights.

Question

Which two scenarios are examples of a conversational AI workload? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. a telephone answering service that has a pre-recorder message
B. a chatbot that provides users with the ability to find answers on a website by themselves
C. telephone voice menus to reduce the load on human resources
D. a service that creates frequently asked questions (FAQ) documents by crawling public websites

Answer

B. a chatbot that provides users with the ability to find answers on a website by themselves
C. telephone voice menus to reduce the load on human resources

Explanation

B: A bot is an automated software program designed to perform a particular task. Think of it as a robot without a body.
C: Automated customer interaction is essential to a business of any size. In fact, 61% of consumers prefer to communicate via speech, and most of them prefer self-service. Because customer satisfaction is a priority for all businesses, self-service is a critical facet of any customer-facing communications strategy.

Not D: Early bots were comparatively simple, handling repetitive and voluminous tasks with relatively straightforward algorithmic logic. An example would be web crawlers used by search engines to automatically explore and catalog web content.

The correct answers are B. a chatbot that provides users with the ability to find answers on a website by themselves and C. telephone voice menus to reduce the load on human resources.

Conversational AI is a type of AI workload that deals with creating natural and engaging interactions between humans and machines using natural language, such as text or speech. Conversational AI can use advanced algorithms to perform various tasks, such as natural language processing, natural language understanding, natural language generation, or speech recognition to create chatbots, voice assistants, or virtual agents.

Two of the scenarios that are examples of a conversational AI workload are:

• A chatbot that provides users with the ability to find answers on a website by themselves: This is a conversational AI workload, as it involves creating a natural language interface for users to interact with a website and get information or assistance. A chatbot can use techniques such as natural language processing, natural language understanding, natural language generation, or natural language querying to process and understand user input, query the website data, and generate a relevant and helpful response.
• Telephone voice menus to reduce the load on human resources: This is a conversational AI workload, as it involves creating a speech-based interface for users to interact with a phone system and get information or assistance. A telephone voice menu can use techniques such as speech recognition, speech synthesis, speech translation, or speech understanding to convert speech to text or text to speech, translate speech between languages, or understand the user’s intent and provide the appropriate option or action.

The other two scenarios are not examples of a conversational AI workload, but of other types of AI workloads:

• A telephone answering service that has a pre-recorded message: This is not a conversational AI workload, but a speech synthesis workload. Speech synthesis is a technique that can generate speech from text, such as reading text messages, emails, or web pages aloud. Speech synthesis can use advanced algorithms to analyze the text and generate a speech output that sounds natural and human-like. Speech synthesis can also use different voices, languages, and accents to customize the speech output. However, speech synthesis does not involve any interaction or dialogue with the user, as the message is fixed and predetermined.
• A service that creates frequently asked questions (FAQ) documents by crawling public websites: This is not a conversational AI workload, but a text generation workload. Text generation is a technique that can generate text from data, such as creating summaries, headlines, or captions. Text generation can use advanced algorithms to analyze the data and generate a text output that is coherent and meaningful. Text generation can also use different styles, tones, and formats to customize the text output. However, text generation does not involve any interaction or dialogue with the user, as the text is created and delivered without any user input.

References

Microsoft Docs > Azure > Architecture > Data Architecture Guide > Artificial intelligence architecture
Microsoft Docs > Azure > Architecture > Interactive voice response app with bot

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