Abstract: AI has a broad range of use cases in operations, production, and supply chain management. However, it is in front-end functions, such as sales and customer support, where organizations are reaping the most rewards from AI. As our world becomes more digital, conversational AI is being used to enable communication between computers and humans. The global reach of business has given rise to a need to train data for AI systems that understand text and speech in multiple languages.
Conversational AI is complex and requires the expertise of developers, data scientists, and when a truly global customer experience is required, linguists. A multilingual chatbot or voice assistant adds a layer of intricacy, given the volume and creation of data needed for ingestion into the machine learning systems required to meet the linguistic requirements and ensure all business and cultural realities are met.
From languages, dialects, and accents to sarcasm, emojis, and slang, there are a lot of factors that can influence—and enhance—the communication between a human and a machine. Conversational AI systems need to keep up with what’s normal and what’s the ‘new normal’ with human communication.
In this session, Magdalena Konkiewicz, Data Evangelist at Toloka, will cover the business benefits of conversational AI, training data to deliver conversational AI in multiple languages, and how to enhance global customer experience.
- The different types of conversational AI and chatbots
- Business benefits of conversational AI
- Training data for AI systems that understand text and speech in multiple languages
Bio: Magdalena is a Data Evangelist at Toloka which is a global data labeling company servicing the needs of approximately 2,000 large and small businesses worldwide.
Toloka helps its customers generate machine learning data at scale by harnessing the wisdom of the crowd from around the world. Toloka is used by organizations in e-commerce, R&D, banking, autonomous vehicles, web services, and more. Toloka relies on a geographically diverse crowd of several million registered users – 200,000 of which are active monthly, on average. The company is incorporated in Switzerland and has its global headquarters in the USA.
Magdalena prior to joining Toloka has worked in many different sectors in technical roles such as NLP Engineer, Developer, and Data Scientist. She has also been involved in teaching and mentoring Data Scientists. Additionally, she contributes to one of the biggest Medium publications Towards Data Science writing about Machine Learning tools and best practices.
Magdalena’s background is in Artificial Intelligence and she holds a Master's degree in this field from Edinburgh University.