From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

Text generation use case

From the course: Understanding Generative AI in Cloud Computing: Services and Use Cases

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Text generation use case

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- [Narrator] Back to text generation using generative AI in the cloud. This is one of the most popular use cases for this technology, applying to chatbot developments. These are just software systems built to communicate with humans. Again, chances are you're already using a chatbot on your phone and in your car. This technology is pervasive. These models can be trained to determine our speech patterns and turn that into usable data. They also can define human-like responses that make them easy to use. Here's a few use cases for this technology to consider. Customer support. We've all dealt with the IVR, or interactive voice response systems, when calling customer service call centers. While these experiences can be frustrating, they're designed to provide you with the ability to get the help you need using automation rather than an actual human. Generative AI systems in the cloud provide the power to chatbots, allowing them to understand voice input and provide valuable responses. While they can never replace humans a hundred percent of the time, they reduce the workload and cost of customer support teams. Virtual assistance. Much like the use case we just covered, these are AI systems typically running in the cloud, assisting you with appointment scheduling, providing recommendations for hotels and restaurants, or even answering common questions like, "What is the rating of X, Y, Z restaurant?," and, "Are there others nearby that have a better rating?" Useful if you're looking for a nice dinner and the best food. Again, they can use large data sets for training to generate the correct responses. They also have the ability to adapt to user preferences over time, such as the type of food you like and the brands of hotel you prefer, even your preferences for a king size bed. Content generation. These systems can be used to create unique content for various applications. The best examples are writing articles, web pages, blog posts, and even descriptions of products and services. Again, training vast amounts of data using trained models can create valuable content for any number of businesses and personal purposes. We can make use of generative AI systems such as ChatGPT, to create helpful content such as writing thank you notes or summarizing an article or a book, it's some handy time saving stuff. Language translations. Although we covered this before, it's helpful to understand the language translation for generative AI systems in the cloud. This is useful when traveling to another country where you may not understand or speak the native language, and supports critical business applications that may have to work across different language groups. These models can learn languages through training, they become better at the language, and are eventually able to recognize and adjust to translation of different dialects. Text generation using generative AI is core to this technology's value. Indeed, it's how most people understand the importance of this technology, and underlines the value of generative AI in the cloud.

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