Dear Readers,
I hope this message finds you well. Today, I have an exciting story to share with you about the power of AI and its ability to transform various aspects of our lives. From deep learning to generative AI, we are now living in an age where AI has the potential to revolutionize nearly everything, from customer support to code generation.
Although AI has become pervasive in recent years, it wasn’t always so advanced. The earliest AI tools had significant limitations, lacking the ability to understand context or improve on their own. For instance, the first chatbots were rule-based, meaning they operated based on predefined rules or scripts. This limited their capabilities to only what was programmed into them.
However, AI-based chatbots have come a long way since then. With advancements in machine learning and deep learning, these chatbots now have a better understanding of natural language. One notable development is the adoption of large language models (LLMs), which leverage massive amounts of data and combine deep learning algorithms, neural networks, and natural language processing techniques to generate human-like responses to queries.
To illustrate this, let’s dive into the example of Watson X Assistant, a conversational AI platform designed to build and deploy AI-powered chatbots. With the emergence of generative AI, Watson X Assistant aims to transform user experiences by delivering more intelligent and human-like responses. One key component of Watson X Assistant is Neural Seek, a search and natural language generation system that integrates with the platform.
To leverage Neural Seek, the first step is setting up Watson X Discovery, where data will be stored. In this example, we use robotic vacuum manuals and customize them to ensure accurate responses. By asking questions like “How do I change the filter?” and “How often should I change the mopping pad?”, we can fine-tune the answers to improve their accuracy.
Next, we move to the initial setup page of Neural Seek, where we pre-fill information and connect with Watson Discovery. The setup process involves determining parameters such as whether to focus on newer or older documents and generating questions based on the data.
After completing the setup, we integrate Neural Seek with Watson X Assistant by importing the open API file and adding the extension. The authentication is set to API key auth, and the Neural Seek API key is provided. Once the extension is added, we can incorporate it into the dialog by creating a new action skill and configuring the Neural Seek search action. This allows Watson X Assistant to seek answers from Neural Seek when there is no matching action in the dialog.
By following these steps, we can enhance the conversational capabilities of chatbots, enabling them to provide accurate and intelligent responses. As demonstrated in the example, the Neural Seek extension successfully generates human-like responses to questions, such as providing instructions on changing the filter or advising on how often to change the mopping pad.
The generative AI capabilities of Neural Seek are truly remarkable, allowing chatbots to carry out conversations with users just as effectively as humans. If you’re interested in learning more about leveraging generative AI with Watson X Assistant, I encourage you to visit the Watson X Assistant page on IBM.com.
Thank you for taking the time to read this story. If you have any questions or would like to see more content like this in the future, please feel free to reach out. Don’t forget to like and subscribe to stay updated on the latest developments in the world of AI.