UniPrompt provides a unified interface to prompt optimization. We have distilled common functions from different algorithms and provide a plug-n-play API to create new algorithms. It also provides an easy way to benchmark different prompt optimization algorithms.
Advancing time series analysis with multi-granularity guided diffusion model; An algorithm-system co-design for fast, scalable MoE inference; What makes a search metric successful in large-scale settings; learning to solve PDEs without simulated data.
Vision Transformers (ViT) have emerged as the de-facto choice for numerous industry grade vision solutions. But their inference cost can be prohibitive for many settings, as they compute self-attention in each layer which suffers from quadratic computational complexity in the number of tokens. On the…
In 2023, the CO2 growth rate was 3.37 ± 0.11 ppm at Mauna Loa, 86% above the previous year, and hitting a record high since observations began in 1958, while global fossil fuel CO2 emissions only increased by 0.6 ± 0.5%. This implies an unprecedented weakening of land and ocean…
The 'AI for Africa' report published by the Global System for Mobile Communications (GSMA), an association of mobile network operators, shows that agriculture and food security takes up 49 percent of all AI deployments followed by climate action and energy use cases at 26 percent…
Microsoft Research and Nissan Motor Corporation have collaborated to develop a machine learning model that improves the accuracy of predicting EV battery degradation by 80%. Learn how this collaboration supports long-term sustainability goals.
An AI enabled digital health solution to address delays in maternal care seeking While being amongst the most developed African countries, Kenya still has one of the world’s highest maternal mortality rates (51x that of the United Kingdom), with over 6,000 women dying during childbirth each…
We explore the use of Large Language Model (LLM-based) chatbots to power recommender systems. We observe that the chatbots respond poorly when they encounter under-specified requests (e.g., they make incorrect assumptions, hedge with a long response, or refuse to answer). We conjecture that such miscalibrated…
In this paper we present a workload estimator based on biological signals - electroencephalographic and eye-tracking. The workload estimator is person- and session- independent, designed to work in a virtual reality flight simulator environment and is a part of our adaptive training system. The novel…
Informal natural language that describes code functionality, such as code comments or function documentation, may contain substantial information about a programs intent. However, there is typically no guarantee that a programs implementation and natural language documentation are aligned. In the case of a conflict, leveraging…
Demand-driven resource allocation for cloud databases has become a popular research direction. Recent approaches have evolved from reactive policies to proactive decision making. These approaches leverage not only the current resource demand but also the predicted demand to make more informed resource allocation decisions for…
RUBICON evaluates AI-driven conversations and improves their quality by learning detailed domain-specific rubrics from minimal data. It gathers insights on AI assistant performance while maintaining user privacy and data security.
