Artificial Intelligence in Enterprise: Basics, NLP, and Chatbots
A recent meetup covered the evolution of AI, what is being done now, as well as pitfalls and success stories of using natural language processing for chatbots.
Below are the videos and slides from an AI/ML meetup held in Amsterdam on June 26, 2018.
Artificial intelligence in enterprise
Mary-Jo Diepeveen, Technology Advisor at Microsoft, started the meetup with an introduction to artificial intelligence (AI). Her talk hit the following points:
- How does AI work? What is machine learning?
- Why is artificial intelligence trending now?
- What’s the view of Microsoft on AI?
- How to start with AI within an enterprise?
Mary-Jo’s slides from her presentation can be found below.
Natural language processing for chatbot implementation
In the following session, Michael George Chaniotakis, a Chatbot Engineer at ABN AMRO, outlined how natural language processing (NLP) has influenced the development of chatbots. The topics in his talk included:
- What is natural language processing?
- When did chatbot development start?
- How can NLP be used for chatbot implementation?
- Case studies: Botakis (“the Cretan who knows everything”) and Anna (ABN AMRO’s chatbot)
Michael’s slides from his presentation can be found below.
Further reading
- Natural Language Processing Saves Businesses Millions of Dollars
- Approaches and Models for Applying Natural Language Processing
- Things That Matter When Building a Natural Language Chatbot
About the experts
Mary-Jo Diepeveen is a technology advisor at Microsoft teaching customers how to use data and artificial intelligence to become more productive and innovative. Her passion for AI comes from the times researching human intelligence, trying to figure out how the brain works and how it guides our behavior. By understanding the brain, Mary-Jo explores how AI models can be used for improving technology in various different scenarios.
Michael George Chaniotakis is a chatbot engineer at ABN AMRO NL, working on the bank’s chatbot Anna. He focuses mainly on fuzzy logic, path planning (biological adaptation), natural language processing, decision-making, multi-agents systems, and neural networks. Currently, Michael is experimenting with artificial general intelligence. His favourite languages are C / C++, Python, Ruby, Java, Scala, JavaScript (Node.js), LISP, and PHP. Michael holds a BSc in Computer Science and Artificial Intelligence, having graduated from the University of Hertfordshire in 2014. He went all way down from a software developer to an AI architect in Crowdpolicy over the past 3.5 years creating crowd-resource, crowd-lending, crowd-funding, and crowd-innovation platforms.
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