Join Allen and Mark as they delve into Voiceflow's groundbreaking new feature: intent classification using a hybrid of LLMs and classic NLU models. Discover how this innovative approach leverages the strengths of both technologies to achieve greater accuracy and flexibility in understanding user intent. How they're doing it just may blow your mind! 🤯 Timestamps: 0:00:00 - Introduction 0:00:33 - Exploring the concept of intents and slots in conversational UI 0:05:11 - Understanding Natural Language Understanding (NLU) and its role in intent classification 0:06:02 - Voiceflow's hybrid approach: Combining classic NLU with LLMs 0:08:36 - Deep dive into Voiceflow's documentation on intent classification using LLMs 0:13:43 - Understanding the hybrid approach and its components: intent descriptions, prompt wrappers, and training data 0:24:31 - How the classic NLU model pre-filters intents for the LLM, improving efficiency and accuracy 0:27:27 - Exploring the user experience and the flow of intent classification with the hybrid model 0:32:53 - Voiceflow's commitment to open research and sharing knowledge with the developer community 0:35:52 - The value of benchmarking and analyzing different LLM models for intent classification 0:39:12 - Call to action: Share your thoughts and experiences with Voiceflow's hybrid approach
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