One of the four pillars of good conversation is levity. You needn't be a comedian, you can but have some fun Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called "TALK: How to talk gooder in business and life", and the author of a new book, Talk: The science of conversation and the art of being ourselves.

Conversational recommender systems (CRSs) aim to provide recommendation services via natural language conversations. Although a number of approaches have been proposed for developing capable CRSs, they typically rely on sufficient training data for training. Since it is difficult to annotate recommendation-oriented dialogue datasets, existing CRS approaches often suffer from the issue of insufficient training due to the scarcity of training data. To address this issue, in this paper, we propose a CounterFactual data simulation approach for CRS, named CFCRS, to alleviate the issue of data scarcity in CRSs. Our approach is developed based on the framework of counterfactual data augmentation, which gradually incorporates the rewriting to the user preference from a real dialogue without interfering with the entire conversation flow. To develop our approach, we characterize user preference and organize the conversation flow by the entities involved in the dialogue, and design a multi-stage recommendation dialogue simulator based on a conversation flow language model. Under the guidance of the learned user preference and dialogue schema, the flow language model can produce reasonable, coherent conversation flows, which can be further realized into complete dialogues. Based on the simulator, we perform the intervention at the representations of the interacted entities of target users, and design an adversarial training method with a curriculum schedule that can gradually optimize the data augmentation strategy. Extensive experiments show that our approach can consistently boost the performance of several competitive CRSs, and outperform other data augmentation methods, especially when the training data is limited. Our code is publicly available at https://github.com/RUCAIBox/CFCRS.

This paper presents a conversational AI platform called Flowstorm. Flowstorm is an open-source SaaS project suitable for creating, running, and analyzing conversational applications. Thanks to the fast and fully automated build process, the dialogues created within the platform can be executed in seconds. Furthermore, we propose a novel dialogue architecture that uses a combination of tree structures with generative models. The tree structures are also used for training NLU models suitable for specific dialogue scenarios. However, the generative models are globally used across applications and extend the functionality of the dialogue trees. Moreover, the platform functionality benefits from out-of-the-box components, such as the one responsible for extracting data from utterances or working with crawled data. Additionally, it can be extended using a custom code directly in the platform. One of the essential features of the platform is the possibility to reuse the created assets across applications. There is a library of prepared assets where each developer can contribute. All of the features are available through a user-friendly visual editor.

In today's competitive market, businesses must ensure that their brand creates a unique experience for customers. Chatbots allow customers to engage with your brand on the internet and get information and suggestion on products or services. All this without getting bogged down with repetitive tasks like waiting on hold or being directed from one department to another. This means that customers get information faster, translating into more sales and better relationships with your company overall. Let's take a real-world example to see how it would work.

Have you ever wondered who designs a chatbot conversation? Who decides what reply the bot will give? How does the chatbot respond? I stumbled upon an opportunity to write conversations for chatbots without any prior technical knowledge. All you need is to be creative with your words and create conversations that are human-centric.

Artificial intelligence has seen a meteoric rise in recent years. From chatbots and marketing initiatives to automating workloads and improving customer service, businesses are increasingly turning to AI to streamline operations, while consumers use AI-driven tech like smart speakers to make their lives easier and more enjoyable. As the technology behind artificial intelligence evolves, developers must continue to consider one of the primary goals of AI development: to make it more "human" than "artificial." More human-like AI is not only more likely to be trusted and adopted by the general public but also provides a smoother, more successful user experience. If you're working to build an AI application that's more "human-centric," keep these 15 important factors shared by the members of Forbes Technology Council in mind.

Whitepapers are designed to be plain-speaking and informative documents spanning an array of subjects. At Creative Virtual, whitepapers are not created too often as they hold a special place in our repository of resources since they offer information that stays valid for a much longer time than other documents. We write them as valuable reference points which can be reviewed when required. We take great pleasure in introducing this newly created whitepaper from Creative Virtual as it has a lot of straight talk about one of our favourite subjects: user experience in the realm of self-help tools. The insight and intel our Guide to Selecting a Virtual Agent or Chatbot Vendor: Forget the Technology & Focus on Experience contains spans the width and breadth of the company: sales, marketing, technical and not least the operations team, some of who contributed by submitting their hottest and most relevant tips. Where else can you find a paper that consolidates industry understanding and expertise from a group of people with a combined 83 years of experience in a field that has only been viable, commercially, for about the past 20?!

Welcome to the world of intelligent chatbots: your companion and conversation agents who should make your life smarter. A leading research paper even said that by 2020, the average person would have more conversations with bots than with their spouse. So, be ready to embrace this new life in a year from now. Have you ever tried telling Siri or Google to "find restaurants that don't serve pizza?" At least they are both consistent in that they gave the same answer -- suggesting restaurants that do serve pizza. The first citizen humanoid robot, Sofia, is making her way to every media event, conducting interviews using human-like conversations. How does she compare to these competitors? Well, the truth is far from reality.

The idea of using chatbots may seem a little daunting at first. You may be thinking that there's no way your business could ever successfully utilize one, that it's way too complicated, and it won't really help the bottom line of your business -- it's simply not true. Chatbots are not as complicated as you might think. We're here to help give you the information you need to leverage this technology, and we'll also demonstrate how chatbots can absolutely improve your bottom line by automating conversations throughout your business. Below, we give you the basics of chatbots, help you articulate your goals, create a plan with some good old-fashioned chatbot strategy, and share industry best practices.

To have an effective conversation, it is important to understand the sentiment and respond appropriately. In a customer service call, a simple acknowledgment when talking to an unhappy customer might be helpful, such as, "Sorry to hear you are having trouble." Understanding sentiment is also useful in determining when you need to hand over the call to a human agent for additional support. To achieve such a conversational flow with a bot, you have to detect the sentiment expressed by the user and react appropriately. Previously, you had to build a custom integration by using Comprehend APIs.