Building on the foundations of deep learning and symbolic AI, we have developed a software able to answer complex questions with minimal domain-specific training. Initial results are encouraging – the system achieves state-of-the-art accuracy on two datasets with no need for specialized training.
The field of Natural Language Processing (NLP) has made large strides over the last decade. In fact, NLP is so common in today’s AI applications that whether consumers are communicating with a virtual assistant, asking for travel directions or searching for weather predictions, chances are they’re interacting with some form of NLP. This technology, however, […]
IBM Research AI is leading the push to develop new tools that enable AI to process and understand natural language. Our goal: empower enterprises to deploy and scale sophisticated AI systems that leverage natural language processing (NLP) with greater accuracy and efficiency, while requiring less data and human supervision.
IBM Fellow Salim Roukos provides some specifics on IBM Research’s enterprise NLP work by highlighting four papers IBM Research AI is presenting at the ACL 2019 conference.