Wearable devices that measure physiological and behavioral signals have become commonplace. There is growing evidence that these devices can have a meaningful impact promoting healthy behaviors, detecting diseases, and improving the design and implementation of treatments. These devices generate vast amounts of continuous, longitudinal, and multimodal data. However, raw data from signals like electrodermal activity […]
Cities face the constant challenge of traffic congestion, which is intrinsically linked to our quality of life. Congested streets impact not only our economies but also the environment and our collective well-being. To build smarter cities, we need a quantitative understanding of how traffic behaves, just as Google’s Project Green Light explores how to improve
Key findings from user studies In addition to simulation experiments, we conducted user studies to test the effectiveness of SpeakFaster. The studies involved both non-AAC and ALS eye-gaze users, because participating in such studies can tax the already-limited time and energy of individuals with ALS that communicate with eye-gaze alone. The 19 non-AAC participants, typing
AI is revolutionizing the landscape of scientific research, enabling advancements at a pace that was once unimaginable — from accelerating drug discovery to designing new materials for clean energy technologies. The AI for Science Forum — co-hosted by Google DeepMind and the Royal Society — brought together the scientific community, policymakers, and industry leaders to
What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and mathematically principled architectures result in only marginal improvements while compute-intensive and engineering-first efforts that scale to ever larger training sets and model parameter counts result
What is the Role of Mathematics in Modern Machine Learning? The past decade has witnessed a shift in how progress is made in machine learning. Research involving carefully designed and mathematically principled architectures result in only marginal improvements while compute-intensive and engineering-first efforts that scale to ever larger training sets and model parameter counts result
The relationships between a population of people, their health outcomes, and their local contexts can be very complex. Nevertheless, developing an understanding of these population dynamics can be crucial for addressing complex social problems, such as disease, economic security, disaster response, and much more. Despite the importance, however, accurate predictions for these population dynamics have
Our work proposes a different rule that slightly, but still not optimally, reduces the potential gains from manipulation. The theoretical rule we propose identifies a small set of teams as “significant”, which we define as teams that could form coalitions that lead to a team in the coalition being the clear winner. We classify each
The ionosphere is a swirling sea of charged particles that lies in Earth’s upper atmosphere. The ions accumulate when solar radiation collides with atmospheric gas molecules, knocking off some of their electrons. Variations in the free electron density across the ionosphere are one of the largest sources of error in satellite navigation systems such as
We introduce Anthology, a method for conditioning LLMs to representative, consistent, and diverse virtual personas by generating and utilizing naturalistic backstories with rich details of individual values and experience. What does it mean for large language models (LLMs) to be trained on massive text corpora, collectively produced by millions and billions of distinctive human authors?
