Research Seminar by Tomas Mikolov | Language Modeling and Artificial Intelligence

Language Modeling and Artificial Intelligence

Statistical language modeling has been labeled as an AI-complete problem by many famous researchers of the past. However, despite all the progress made in the last decade, there are still difficult scientific challenges in front of us that have to be solved in order to achieve truly intelligent models of language. We need to focus on developing new mathematical models with certain properties, such as the ability to learn continually and without explicit supervision, generalize to novel tasks from limited amounts of data, and the ability to form non-trivial long-term memory. The speaker will describe some of their early attempts to develop such models within the framework of complex systems.

About the Speaker

Tomas Mikolov is a researcher at Czech Institute of Informatics, Robotics and Cybernetics (CIIRC), Czech Technical University in Prague. Currently, he leads a research team focusing on development of novel techniques within the area of complex systems, artificial life and evolution. Previously, he did work at Facebook AI and Google Brain, where he led development of popular machine learning tools such as word2vec and fastText. He obtained his PhD degree at the Brno University of Technology in 2012 for his work on neural language models, which was open sourced as the RNNLM project. This was the first project that introduced ideas such as text generation from neural language models, gradient clipping, dynamic model evaluation or scalable implementation which allowed training large scale models. His main research interest is to understand intelligence, and to create artificial intelligence that can help people to solve complex problems.