LiveChatAI: An Innovative AI Chatbot LiveChatAI allows you to create an AI chatbot trained with your own data and combines AI with human support. Data sources, like websites, text, PDFs, and Q&A, can help you ease the process and engage with the audience by using the right informatio...
A dataset for training customer service chatbot models on LLMs - bitext/customer-support-llm-chatbot-training-dataset
This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluated based on its sparse-categorical loss during training and BLEU in the inference phase, utilizing a neural generative attention-based ...
Feed in data to instruct your conversational chatbot dataset and facilitate continuous improvement of your bot’s ability to speak like a human. Agent Hand-off Pass the conversation over to customer service representatives at the appropriate moment, without losing context. Multilingual Chatbots ...
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily cont... SM Suhaili,...
AI chatbots could manage intricate, real-time conversations, while digital twins could model and optimize workflows to ensure everything runs smoothly behind the scenes. But let’s be realistic: even the smartest AI won’t fully replace human agents anytime soon. Customers still value empathy ...
The dataset used in this project is theBitext Customer Support LLM Chatbot Training Dataset. Fields of the Dataset Each entry in the dataset contains the following fields: flags: Tags associated with the entry (explained below in the Language Generation Tags section). ...
In aglobal consumer channel preferences study, it was found that Millennials and Gen Z were the most likely to prefer talking to chatbots. The proportion of people who don’t mind interacting with a support chatbot before speaking to a human agent. ...
KARAKURI built an LLM (karakuri-ai/karakuri-lm-70b-chat-v0.1) to create customer support chatbots that not only have Japanese proficiency but also respond with a helpful demeanor. Meanwhile, Watashiha injected a dose of humor into the AI realm, developing OGIRI—a humor-focused foundation model...
With gradually developed ability to learn from the large dataset, AI email support can offer certain meaningful solutions just like chatbots. It can suggest a help article using natural language processing system. It can even fetch some part of email draft for people working in a call center. ...