Augmenting large language models (LLMs) with external tools, rather than relying solely on their internal knowledge, could unlock their potential to solve more challenging problems. Common approaches for such “tool learning” fall into two categories: (1) supervised methods to generate tool calling functions, or (2) in-context learning, which uses tool documents that describe the intended […]
Quantum computers have the potential to revolutionize drug discovery, material design and fundamental physics — that is, if we can get them to work reliably. Certain problems, which would take a conventional computer billions of years to solve, would take a quantum computer just hours. However, these new processors are more prone to noise than
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
