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How to build an AI chatbot in just 5 mins

How to build a chat bot in just 5 mins using Watson X and Neural Seek

The evolution and application of artificial intelligence (AI), particularly in the realm of chatbots, has seen a significant transformation over the years. This transformation has been largely driven by the shift from rule-based systems to learning-based systems, with the introduction of large language models (LLMs) and platforms like Watson X Assistant.

This article will delve into the evolution of AI, the role of LLMs, the introduction of Watson X Assistant, and the use of generative AI in enhancing user experiences. In the video below IBM provide a demonstration of setting up Watson X Discovery and Neural Seek, and how these tools can be integrated to improve the accuracy of responses.

The age of AI has brought about significant advancements in various fields, including customer support and code generation. Early AI tools, however, had limitations, such as the inability to understand context or learn and improve independently. Initial chatbots were rule-based, developed on predefined rules or scripts, limiting their capacity to what was programmed into them. This meant that their responses were often rigid and lacked the ability to understand and respond to nuanced queries.

How to build a chat bot in just 5 mins

The evolution of AI-based chatbots has seen a shift from these rule-based systems to learning-based systems. These systems leverage machine learning and deep learning to improve natural language understanding. Large Language Models (LLMs) are at the forefront of this shift. LLMs use vast amounts of data, deep learning algorithms, neural networks, and natural language processing techniques to generate human-like responses. This has significantly improved the capabilities of chatbots, allowing them to understand and respond to a wider range of queries with greater accuracy.

Learn more about building your very own AI chatbots using the latest AI tools at your disposal :

One such platform that leverages the power of LLMs is Watson X Assistant, a conversational AI platform designed to build and deploy AI-powered chatbots. Watson X Assistant not only uses LLMs but also incorporates generative AI to transform user experiences by delivering more intelligent, human-like responses. This has significantly improved the user experience, making interactions with chatbots more engaging and productive.

To further enhance the capabilities of Watson X Assistant, it can be integrated with Neural Seek, a search and natural language generation system. Watson X Discovery is used to store data, which can be tested and improved upon. The Neural Seek extension can be added to Watson X Assistant to enhance its dialog capabilities. This extension can be configured to seek answers from Neural Seek when it can’t match any phrases to those set up in Watson X Assistant. This ensures that the chatbot can provide accurate responses even to complex or nuanced queries.

The integration of Neural Seek with Watson X Assistant significantly improves the accuracy of responses. The Neural Seek extension can help chatbots carry out conversations as effectively as humans due to its generative AI capabilities. This means that chatbots can not only understand and respond to a wide range of queries but also learn and improve over time, making them more effective and efficient.

The evolution and application of AI in chatbots have seen significant advancements with the introduction of learning-based systems, LLMs, and platforms like Watson X Assistant. The integration of Watson X Assistant with Neural Seek further enhances these capabilities, delivering more accurate and human-like responses. For those interested in learning more about leveraging generative AI with Watson X Assistant, more information can be found on the IBM website. This marks an exciting era in the field of AI, with the potential for further advancements and improvements in the years to come.

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A chatbot prepares a ‘shotgun sermon’ for Texas churchgoers.

The ChatGPT service was called a “shotgun sermon” by Pastor Jay Cooper.
A church in Texas held a Sunday service that was completely computerized.

According to a story from KXAN, pastor Jay Cooper of the Violet Crown City Church in north Austin used ChatGPT to create a lecture, saying he got the idea after reading about the technology and thinking what it would be like to use it during a service.

Cooper said, “ChatGPT put out about a 15-minute service, like a shotgun sermon, an outline.” “It’s clear that there still needs to be a human factor. I had to add more questions to the service and a few to the lecture to make it more interesting.

The popularity of ChatGPT, an OpenAI-made AI robot, has increased recently. People have used the service to help with a wide range of tasks, like coming up with ideas or making plans for articles, essays, and even books. Some people have used ChatGPT or similar tools to write whole papers and books, while others have used the technology to help with study.

“AI can be used in so many different ways,” Cooper said. “I just had the idea, ‘What would it look like to use this in a worship service?’”

Cooper said that he talked to members of the church before trying the service. However, some people said later that AI would have a hard time removing the human part.

Ernest Chambers, who went to the service, told KXAN, “I’m not sure that AI can really show love, kindness, and empathy.” “I think we should show love and put it into action. We must not only feel it, but also show it.”
Cooper thinks that the trial was a chance for him and the other people there to learn more about what it means to pray.

“A big question I have about letting AI lead service is whether or not a prayer made by AI can somehow tell the truth. Can you have a relationship with God that way?” Cooper inquired.
Cooper said that it’s possible that lectures made by AI could pick up on parts that people find meaningful. This could help people become more open to new ideas and ways of thinking.

Cooper said, “Maybe something speaks to them, and that makes them think, maybe I’m not looking for the sacred enough in the rest of the world.”

Cooper said that using AI for the service was a one-time thing and that he has no plans to do something similar.