Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. NEW RESEARCH Adaptive Security, Erasures, and Network Assumptions in Communication-Local MPC n-party Multi-Party Computation (MPC) is a cryptographic protocol technique that allows separate parties to securely compute a function on their joint data while keeping their inputs private. To build such a protocol,  

Introduction Generative foundation models have transformed various domains, creating new paradigms for content generation. Integrating these models with domain-specific data enables industry-specific applications. Microsoft Research has used this approach to develop the large market model (LMM) and the Financial Market Simulation Engine (MarS) for the financial domain. These innovations have the potential to empower financial researchers to customize generative models for diverse scenarios, establishing a new paradigm for applying generative models to downstream tasks in financial markets. This integration may […]

Groundbreaking advancements in frontier language models are progressing rapidly, paving the way for boosts in accuracy and reliability of generalist models, making them highly effective in specialized domains. As  

The Global Health Drug Discovery Institute (opens in new tab) (GHDDI) and Microsoft Research have reached a milestone in tuberculosis (TB) drug research with TamGen (opens in new tab), an open-source (opens in new tab), transformer-based chemical language model for developing target-specific drug compounds. Working in collaboration, the joint team successfully identified several promising inhibitors for a TB protease, with the most  

# Factors to Consider When Selecting a Health Insurance Plan During Open Enrollment for 2024  Selecting a health insurance plan during the open enrollment period can be a complex process, but understanding the key factors to consider can help individuals make informed decisions. Here are some important aspects to keep in mind:  ## Coverage and Networks  One of the primary considerations is the coverage network of the plan. Insurers form coverage networks of hospitals and doctors, and it is crucial to ensure that […]

Earlier this year, Microsoft Research announced (opens in new tab) its newest lab in Tokyo, Japan. Today, we are celebrating its grand opening, reinforcing Microsoft Research’s commitment to AI research across the Asia-Pacific region. This new lab will focus on embodied AI, well-being and neuroscience, societal AI, and industry innovation—all areas that align with Japan’s socioeconomic priorities. This initiative will enhance collaboration with local academic and industrial partners, contributing to global innovation and talent development.  We recently spoke with Yasuyuki […]

In cancer diagnosis or advanced treatments like immunotherapy, every detail in a medical image counts. Radiologists and pathologists rely on these images to track tumors, understand their boundaries, and analyze how they interact with surrounding cells. This work demands pinpoint accuracy across several tasks—identifying whether a tumor is present, locating it precisely, and mapping its contours on complex CT scans or pathology slides.  Yet, these crucial steps—object recognition, detection,  

Retrieval-augmented generation (RAG) allows AI systems to provide additional information and context to a large language model (LLM) when generating a response to a user query. However, traditional RAG-based methods  

Our work on Orca and Orca 2 demonstrated the power of using synthetic data for the post-training of small language models and getting them to levels of performance previously found only in much larger language models. Orca-AgentInstruct is another step in this direction, where we explore using agentic flows to generate diverse and high-quality data at scale. Orca-AgentInstruct is an agentic solution for synthetic-data generation. By leveraging an agentic framework, AgentInstruct can generate tailored datasets, comprising both prompts and responses, […]

Today, development of generalizable AI models requires access to sufficient data and compute resources, which may create challenges for some researchers. Democratizing access to technology across the research community can advance the development of generalizable AI models. By applying the core software development concept of modularity to AI, we can build models that are powerful, efficient, adaptable, and transparent.  Until recently, AI models were primarily built using monolithic architecture. Though powerful, these models can be challenging to customize and edit […]