Faculty Summit 2017
July 17, 2017 - July 18, 2017

Faculty Summit 2017: The Edge of AI

Lieu: Redmond, WA

2017 Faculty Summit AgendaDownload the agenda

Contact us: If you have questions about this event, please send us an email at [email protected]

Past events:
Faculty Summit 2016
Faculty Summit 2015
Faculty Summit 2014
Faculty Summit 2013
Faculty Summit 2012
Faculty Summit 2011
Faculty Summit 2010
Faculty Summit 2009

Faculty Summit 2017: The Edge of AI

The 18th annual Microsoft Research Faculty Summit was held in Redmond, WA on July 17 and 18, 2017 and consisted of a variety of keynotes, talks, panels, and technologies focused on Artificial Intelligence (AI) research: The Edge of AI.

Microsoft AI researchers are striving to create intelligent machines that complement human reasoning and enrich human experiences and capabilities. At the core, is the ability to harness the explosion of digital data and computational power with advanced algorithms that extend the ability for machines to learn, reason, sense, and understand—enabling collaborative and natural interactions between machines and humans.

We are seeing widespread investments in AI which are advancing the state of the art in machine intelligence and perception, enabling computers to interpret what they see, to communicate in natural language, to answer complex questions, and to interact with their environment. In addition to technological advances, researchers and thought leaders need to be concerned with the ethics and societal impact of intelligent technologies.

The Microsoft Research Faculty Summit 2017 brought together thought leaders and researchers from a broad range of disciplines including computer science, social sciences, human design and interactions, and policy. Together we highlighted some of the key challenges posed by artificial intelligence and identified the next generation of approaches, techniques, and tools that will be needed to develop AI to solve the world’s most pressing challenges.

Focus Areas

We explored the following areas:

  • Machine learning – Developing and improving algorithms that help computers learn from data to create more advanced, intelligent computer systems.
  • Human language technologies – Linking language to the world through speech recognition, language modeling, language understanding, and dialog systems.
  • Perception and sensing – Creating computers and devices which understand what they see to enable tasks ranging from autonomous driving to analysis of medical images.
  • AI, people, and society – Examining the societal and individual impacts on the spread of intelligent technologies to formulate best practices for their design.
  • Systems, tools and platforms – Integrating intelligent technologies to create interactive tools such as chatbots that incorporate contextual data to augment and enrich human reasoning.
  • Integrative intelligence – Weaving together advances in AI from disciplines such as computer vision and human language technologies to create end-to-end systems that learn from data and experience.
  • Cyber-physical systems and robotics – Developing methods to ensure the integrity of drones, robots and other intelligent technologies that interact with the physical world.
  • Human AI collaboration – Harnessing research breakthroughs in artificial intelligence to design technologies that allow humans to interact with computers in novel, meaningful and productive ways.
  • Decisions and planning – Reasoning about future events to enable informed collaborations between humans and intelligent agents.

Program Chairs