Systems that learn and reason

After the amazing breakthroughs of machine learning (deep learning or otherwise) in the past decade, the shortcomings of machine learning are also becoming increasingly clear: unexplainable results, data hunger and limited generalisability are all becoming bottlenecks.

In this talk we will look at how the combination with symbolic AI (in the form of very large knowledge graphs) can give us a way forward, towards machine learning systems that can explain their results, that need less data, and that generalise better outside their training set.

Talk+Live Q&A at the Plaza in Connected Data World Center

You need an access pass to attend this session: Diversity Access Pass or Full Access Pass apply