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Artificial Intelligence

Allen School researchers are at the forefront of exciting developments in AI spanning machine learning, computer vision, natural language processing, robotics and more.

We cultivate a deeper understanding of the science and potential impact of rapidly evolving technologies, such as large language models and generative AI, while developing practical tools for their ethical and responsible application in a variety of domains — from biomedical research and disaster response, to autonomous vehicles and urban planning.


Groups & Labs

Robotic arm feeding seated person a strawberry on a fork with an inset image of the robot mapping features of their face

Personal Robotics Lab

Our mission is to develop the fundamental building blocks of perception, manipulation, learning, and human-robot interaction to enable robots to perform complex physical manipulation tasks under clutter and uncertainty with and around people.

A robot playing table tennis with human partner

Social RL Lab

The Social RL Lab aims to leverage social information in human-AI and multi-agent interactions to enable AI to learn complex behavior, rapidly adapt to new circumstances and cooperate to achieve joint goals—similarly to how humans and animals learn.


Faculty Members

Faculty

Faculty

Faculty


Centers & Initiatives

The Science Hub supports a broad set of programs — including fellowships for doctoral students, collaboration among researchers and support for collaborative research events — designed to accelerate artificial intelligence (AI), robotics and engineering in the Seattle area.

Society + Technology is a cross-campus, cross-disciplinary initiative and community at the University of Washington that is dedicated to research, teaching and learning focused on the social, societal and justice dimensions of technology.

Highlights


Allen School News

A team of Allen School and Ai2 researchers were recognized for developing an efficient, scalable system for indexing petabyte-level text corpora with minimal storage overhead to better understand the data on which large language models are trained.

Allen School News

Allen School researchers led the development of a benchmark dataset of 26,000 real-world, open-ended queries to evaluate the creative generation of large language models. They discovered major LLMs all generate similar outputs as if they’re part of an Artificial Hivemind.

Business Insider

Farhadi, who co-leads the Allen School’s Reasoning, AI, and VisioN (RAIVN) Lab and is also CEO of the Allen Institute for Artificial Intelligence (Ai2), was recognized for his leadership in open AI research and his influence on how institutions scale AI for the benefit of humanity.