How to implement chatbots in an industrial context
Chatbots are among the most popular applications of artificial intelligence, machine learning, and natural language processing, and many people are already familiar with them. Various companies are developing first prototypes to improve their customer communication and support functions. How do we begin to implement them into an industrial context?
Chatbots applications are everywhere. But running a tutorial or using a predefined cloud service is something fundamentally different than implementing a productive chatbot for a real-world application that is scalable, continuously improvable, and integrated into the company’s core IT architecture.
In his presentation, Christoph Windheuser talks about the experience ThoughtWorks has made in several chatbot projects. First, he goes over why the definition of the character of the bot is one of the most important design principles, followed by what the architecture of a bot looks like. He will also talk about what can be done with machine learning algorithms and where the limits of this approach are today. Then he will go over why testing a chatbot is difficult, as well as how to run test-driven development and continuous delivery and how to continuously improve the performance of the bot with continuous intelligence.
Christoph Windheuser will illustrate this talk with a live demonstration of one of ThroughtWorks’ chatbots.
Christoph Windheuser is the Global Head of Artificial Intelligence at ThoughtWorks Inc. Before joining ThoughtWorks, he held several positions at SAP and Capgemini. Before that, he completed his PhD in Neural Networks with a focus on Speech Recognition.