Printed circuit boards (PCBs) make up a substantial amount of electronic waste (e-waste) generated annually. Waste PCBs contain high quantities of copper and gold in comparison to natural ores. As such, “urban mining” of waste PCBs to recover these metals is of commercial interest. In…
This work aims at decreasing the end-to-end generation latency of large language models (LLMs). One of the major causes of the high generation latency is the sequential decoding approach adopted by almost all state-of-the-art LLMs. In this work, motivated by the thinking and writing process…
Deciding between fundamental and applied research is a dilemma that confronts many in the scientific community. Dongqi Han, on the cusp of graduation, ambitiously aspired to bridge this divide by pursuing both avenues of research in his future endeavors. After a comprehensive evaluation, Dongqi Han…
Researcher Michel Galley explores how he and fellow researchers combined new and existing data to create MathVista, an open-source benchmark for measuring the mathematical reasoning capabilities of foundation models in scenarios that involve text and images.
Workplace social media platforms enable employees to cultivate their professional image and connect with colleagues in a semi-formal environment. While semi-formal corporate communication poses a unique set of challenges, large language models (LLMs) have shown great promise in helping users draft and edit their social…
Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications. This widespread adoption has spurred extensive research into LLMs across various disciplines, including the social sciences. Notably, studies have revealed that…
The ability to recover MRI signal from noise is key to achieve fast acquisition, accurate quantification, and high image quality. Past work has shown convolutional neural networks can be used with abundant and paired low and high-SNR images for training. However, for applications where high-SNR…
Generative AI is unlocking new research tools for bold scientific discoveries. We sort through the hype and take a deep dive into some practical examples of groundbreaking research enabled by generative AI such as small molecular inhibitors for treating infectious disease and the discovery of…
The impact of technology on mental health has become a core concern for researchers and practitioners from the clinical science, public health and technology sectors. One factor that influences this impact is the large gap between the silos of technologies explicitly designed as mental health…
The Appropriate Reliance research initiative focuses on advancing research and creating practical solutions for fostering appropriate reliance on AI. Through appropriate reliance (opens in new tab), we aim to help people who use AI systems find a balance between over-trusting AI outputs and accepting them…
Large language model-powered tools like Copilot have the potential to increase labor productivity more than any technology in a generation. Motivated by the significance of this moment, researchers from across Microsoft have come together to measure and improve the productivity impacts of Copilot, as well…
Examining how AI can and should influence software engineering - including its effects on developers, how it improves developer efficiency, how it can assist in keeping software safe, and what the potential risks are.
