Research Talk: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Conversation is key to innovation. At Google Berlin, we are organizing this Research Talk Series to share our work and to engage with the local research and engineering community. The talks provide the opportunity to find out more about the challenging problems we are working on, approaches, utilized techniques, results, applications in products, fundamental research as well as research developments and innovation across a range of computer science disciplines. We invite researchers and engineers from academia and industry to this talk. Join us for an opportunity to connect with members of Google’s engineering team, as well as your peers from the region.

Registration starts at 5:30 p.m. and the talk will begin at 6:00 p.m.. Food and drinks will be provided before and after the talk.

Please confirm your attendance on the guest list by REGISTERING BY 25 June 2019. Please note that the number of seats is limited.

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Pre-trained word embeddings have been critical in the success of deep learning for NLP, since they allow models to take advantage of the nearly unlimited amount of unannotated text on the web. In the last few years, conditional language models have been used to generate pre-trained contextual representations, which are much richer and more powerful than plain embeddings. This talk describes BERT (Bidirectional Encoder Representation from Transformers), a new pre-training technique which generates deeply bidirectional pre-trained language representations. BERT obtains state-of-the-art results on the Stanford Question Answering Dataset, MultiNLI, Stanford Sentiment Treebank, and many other tasks.

We look forward to seeing you!

Beate, Benjamin & The Google Research Team

Email to bhuetteroth@google.com

Agenda