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New Conversational UX Stack: Integrating NLU, LLMs, & RAG | by Stefan Kojouharov | Mar, 2024

28Mar

By Stefan KojouharovNo Comments

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New Conversational UX Stack: Integrating NLU, LLMs, & RAG | by Stefan Kojouharov | Mar, 2024

Large Language Models are redefining how we build Conversational Agents. Today, LLMs can do most of the heavy lifting in minutes. The days of building hundreds of flows of every useful intent or FAQ question are gone. Instead, LLMs can be trained on a knowledge base and be able to give great answers.The role of a Conversation Designer has changed. Designers now have to start thinking differently. Instead of thinking linearly and having a flow-based approach to design, now we need to think more about knowledge, information, and data and how all of this leads to meaning-making.Through stories, knowledge bases, and prompt engineering, designers will soon be creating experiences we once only dreamed of. The job has changed, and it is now more creative than ever.Conversational AI Project will c...

Understanding the Intent in NLU. in NLU and Dialogue methodology | by Raphael Pinto | Sep, 2021

in NLU and Dialogue methodologyFirstly... What history is this “NLU and Dialogue methodology”? This post is a continuation of Understanding chatbots solutions in the market. For not to be without understanding, read it before(I recommend!!).Then let’s go… Like I already defined in another story the intent is the objective of the user when he expressed a sentence.For example, considers that we are in a banking context:User: What is my account balance?In this case, we can understand that the user’s desire is to know the amount of money has in your banking account. That is intent. And the output can be:INTENT: ACCOUNT_BALANCE (98%)The user could have expressed for many different modes to ask your account balance. In this methodology, the NLU must comprehend his interactions and choose the int...

How Rasa NLU is moving past Intents | by Stefan Kojouharov | Apr, 2021

If you have ever developed a Conversational AI agent using NLU, you know how often users don’t follow the happy path.They may say or type responses that make perfect sense however their responses still fall outside of any intent.For example, if a user asks about a refund, by typing just their order number, what happens?What is the intent of that message?Obviously, the order number is an entity but since there isn’t a clear intent that it’s mapped to, it will trigger a retrieval action that combines all of your intents into a single FAQ and in this way we have already moved past intents and right into context!RASA is taking this insight to the next level and on May 25th, Alan Nickole, the co-founder and CTO or Rasa will share how RASA is moving beyond intents and using context!Alan Nickole,...