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
Sensor Systems Laboratory
The Sensor Systems Laboratory invents new sensor systems, devises new ways to power and communicate with them, and develops algorithms for using them, with applications in the domains of bioelectronics, robotics, and ubiquitous computing.
RAIVN Lab
The Reasoning, AI, and VisioN (RAIVN) Lab directed by Prof. Ali Farhadi and Prof. Ranjay Krishna focuses at the intersection of computer vision, machine learning, natural language processing and robotics and is targeted towards helping computers…
Faculty Members
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Centers & Initiatives
The AI Institute for Societal Decision Making (AI-SDM) brings together AI and social sciences researchers to develop human-centric AI for societal good that harnesses the power of data and improved understanding of human decisions to create better and more trusted choices.
The Institute for Medical Data Science (IMDS) is a joint effort among the Schools of Medicine and Public Health and the College of Engineering, including the Allen School to lead the development and implementation of cutting-edge AI and data science methods in medical data science. By harnessing the power of AI across diverse health determinants, IMDS aims to improve patient health, provider satisfaction, and healthcare operations, particularly in the Pacific Northwest region.
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.