Efficient Large-Scale AI Workshop

The AI landscape has been transformed by the advent of large-scale models like BERT, Turing, and GPT. Researchers have brought language models to new heights in terms of performance, propelling advancements in search, translation, code generation and more. As models grow in size and capability, their applications are also expanding.

At Microsoft Research, we are approaching large-scale AI from different perspectives, which include not only creating bigger, more powerful models, but also developing new algorithms and approaches to AI development with the goal of delivering meaningful improvements to the way people interact with their worlds, while accounting for the effects they will have on people and society.

The workshop will facilitate knowledge sharing and in-depth discussions about ongoing and future work aiming to develop new technology to bring the benefits of large-scale AI to an expanding set of people in an expanding set of scenarios.

Speakers

Yoav Artzi

Associate Professor
Cornell University

Hany Awadallah

Partner Research Manager Azure AI Cognitive Services

Cristina Garbacea

PhD candidate
University of Michigan Ann Arbor

Song Han

Associate Professor Massachusetts Institute of Technology

Julia Hockenmaier

Professor
University of Illinois at Urbana-Champaign

Mojan Javaheripi

Incoming Researcher Microsoft Research Redmond

Young Jin Kim

Principal Researcher Microsoft Machine Translation

Julia Kiseleva

Senior Researcher
Microsoft Research – Redmond

Edoardo Ponti

Assistant Professor University of Edinburgh

Colin Raffel

Assistant Professor
University of North Carolina at Chapel Hill

Agenda

Workshop organizers

Alessandro Sordoni, Microsoft Research Montréal
Subho Mukherjee, Microsoft Research Redmond
Xiaodong Liu, Microsoft Research Redmond
Yu Cheng, Microsoft Research Redmond
Julia Kiseleva (opens in new tab), Microsoft Research Redmond
Nicolas Le Roux, Microsoft Research Montréal
Ahmed Awadallah, Microsoft Research Redmond

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