Research at Microsoft 2024: Meeting the challenge of a changing world

We live in a rapidly changing world.

Demographic shifts, climate change, political dynamics, and many other forces are creating urgent challenges in critical areas like global health and scientific discovery, environmental sustainability, food security, and societal resilience.

In this new AI era, technology is changing even faster than before, and the transition from research to reality, from concept to solution, now takes days or weeks rather than months or years.

“Today we are seeing so much AI research happening at the speed of conversation, to the point where even our top researchers feel that their heads are spinning, but working together, providing openness, providing greater access, we can see that we’ve made tremendous progress.”

Peter Lee, President, Microsoft Research

In 2024, Microsoft Research continued its foundational research (opens in new tab) to expand the capabilities of large language models, but we also explored more deeply how smaller models (opens in new tab) can be trained for specific tasks. We discovered that by using smaller datasets and fewer compute resources, some small language models can demonstrate enhanced reasoning and other complex capabilities that were once considered the exclusive province of large-scale models.

Microsoft Research and its external collaborators used AI to enable earlier detection and treatment of esophageal cancer, which could lead to dramatically improved survival rates, and to accelerate the discovery of new drugs needed to treat infectious diseases that kill millions of people every year. And we continued to use AI to develop new tools for scientific discovery so that we and others in the scientific community can confront some of humanity’s most important challenges.

One team of Microsoft researchers created the world’s first large-scale model of the atmosphere, which could transform weather forecasting and our ability to predict and mitigate the effects of extreme weather events. Another team worked with global experts to create a generative AI tool that empowers non-governmental organizations (NGOs) to fight human trafficking.

We also opened a new research lab in Tokyo this year. It joins our other labs in Europe, Asia, Africa, and North America. And we launched a series of quarterly Research Forums to help update the global research community about some of the pivotal work we’re doing at Microsoft Research. Register for future episodes, view presentations from previous forums, and explore our briefing book content.

This post highlights some of the work that Microsoft Research has done in 2024, along with academic and industry colleagues, to help drive real-world benefits for people worldwide.


AI for Business Transformation: Multimodal Models


Top social posts of 2024

Students working at computer tables in a classroom

Microsoft Research program encourages AI development by academics, not just industry.

Ece Kamar on the future of AI agents

photo of Ece Kamar

Introducing BitNet b1.58

1.58-bit LLMs that rival full-precision Transformer LLMs in performance while significantly boosting efficiency—in terms of latency, throughput, memory and energy consumption.

Phi-4

A small language model that performs as well as (and often better than) large models on certain types of complex reasoning tasks.

Q-Sparse

A breakthrough in training fully sparsely-activated LLMs supports both full-precision and 1-bit LLMs.

You Only Cache Once (YOCO)

A novel decoder-decoder architecture for LLMs, enhancing memory efficiency by caching key-value pairs only once.

Differential Transformer

A new foundation architecture for LLMs that enhances focus on relevant information while canceling attention noise.

AI Controller Interface

Helping researchers and developers efficiently implement existing strategies for controlling LLMs and invent new ones.

GraphRAG 1.0

Advancing AI use in complex domains like science.

MatterSimV1

A deep learning atomistic model across elements, temperatures, and pressures.

Top stories of 2024

GHDDI and Microsoft Research use AI to achieve progress in new drug discovery for global infectious diseases

GHDDI name and logo on the left with a rainbow spectrum colored honeycomb on the right on a green and blue gradient background

The joint team designed several chemical compounds that are effective in inhibiting these pathogens’ essential target proteins, accelerating the structure-based drug discovery process.

  • various abstract 3D shapes on a light blue background Event Microsoft Research Forum | Episode 1 

    Leading researchers at Microsoft explored the latest breakthroughs in AI models, new applications of AI to important scientific challenges, novel approaches to model evaluation and understanding, and other key research topics.

GraphRAG: Unlocking LLM discovery on narrative private data

Project Ire - GraphRag background: Blue-green gradient

GraphRAG is a significant advance in enhancing the capability of LLMs and enables us to answer important classes of questions that we cannot attempt with baseline RAG alone.

  • News 3 big AI trends to watch in 2024 

    This year, AI is expected to become more accessible, nuanced, and integrated in technologies that improve everyday tasks and help solve some of the world’s most challenging problems.

Scaling early detection of esophageal cancer with AI

white icons of first aid kit, DNA strand, laptop monitor with overlapping eye, and microscope on a blue and green gradient background

Our collaboration with Cyted demonstrates the transformative potential of integrating advanced AI models into clinical workflows. Earlier detection of cancer and earlier start of treatment mean that more than 9 in 10 patients survive 5 years after diagnosis.

  • Research Forum | Episode 2 - abstract chalkboard background Event Microsoft Research Forum | Episode 2 

    Leading researchers at Microsoft discussed how AI is transforming health care and the natural sciences, the intersection of AI and society, and the continuing evolution of foundational AI technologies.

SIGMA: An open-source mixed-reality system for research on physical task assistance

Blue, purple, pink gradient background with three images: a five item checklist on the left, a sound wave in the middle, and goggles on the right.

Imagine if every time you needed to complete a complex physical task you had a world-class expert standing over your shoulder and guiding you through the process. What would it take to build an interactive AI system that could assist you with any task in the physical world? 

  • Microsoft Research Podcast | Ideas | Kalika Bali Podcast Ideas: Language technologies for everyone with Kalika Bali 

    The new series “Ideas” debuts with guest Kalika Bali. The speech and language tech researcher talks sci-fi and its impact on her career, the design thinking philosophy behind her research, and the “outrageous idea” she had to work with low-resource languages.

MatterSim: A deep-learning model for materials under real-world conditions

The image features a complex network of interconnected nodes with a molecular structure, illuminated in blue against a dark background.

The model efficiently handles simulations for a variety of materials, including metals, oxides, sulfides, halides, and their various states such as crystals, amorphous solids, and liquids.

  • Digital pathology helps decode tumor microenvironments for precision immunotherapy. GigaPath is a novel vision transformer that can scale to gigapixel whole-slide images by adapting dilated attention for digital pathology. In joint work with Providence and UW, we’re sharing Prov-GigaPath, the first whole-slide pathology foundation model pretrained on large-scale real-world data, for advancing clinical research and discovery. Blog GigaPath: Whole-Slide Foundation Model for Digital Pathology 

    The confluence of digital transformation in biomedicine and the current generative AI revolution creates an unprecedented opportunity for drastically accelerating progress in precision health. Prov-GigaPath attains state-of-the-art performance on standard cancer classification and pathomics tasks, as well as vision-language tasks.

Aurora: The first large-scale foundation model of the atmosphere

satellite image of Storm Ciarán

Aurora presents a new approach to weather forecasting that could transform our ability to predict and mitigate the impacts of extreme events. The model can forecast a broad range of atmospheric variables, from temperature and wind speed to air-pollution levels and concentrations of greenhouse gases.

  • Research Forum | Episode 3 - abstract chalkboard background with colorful hands Event Microsoft Research Forum | Episode 3 

    Leading researchers at Microsoft dove into the importance of globally inclusive and equitable AI, shared updates on AutoGen and MatterGen, explored novel use cases for AI, and more.

Data-driven model improves accuracy in predicting EV battery degradation

MSRA - Nissan | data driven model improves accuracy in predicting ev battery degradation | graphic with white icons symbolizing renewable electric energy on a blue and green gradient background

Microsoft Research collaborated with Nissan Motor Corporation to develop a new machine learning method that predicts battery degradation with an average error rate of just 0.94%, significantly bolstering Nissan’s battery recycling efforts.

  • white line icons on blue and green gradient background Blog Tracing the path to self-adapting AI agents 

    Trace is a new AutoDiff-like tool for training AI systems without using gradients. This generalization is made possible by OPTO, which can describe end-to-end optimization of AI systems with general feedback.

Male Doctor Using Computer At Desk In Hospital

Imagine if pathologists had tools that could help predict therapeutic responses just by analyzing images of cancer tissue. By leveraging AI and machine learning, researchers are now able to analyze digitized tissue samples with unprecedented accuracy and scale, potentially transforming how we understand and treat cancer.

Find My Things: New teachable AI tool helps blind and low-vision people locate lost personal items

Find My Things - close up of a person's hand taking a photo of keys on a table

Find My Things makes it easy for people with vision disabilities to use their phones to recognize and locate the personal items they use every day.

  • Research Forum | Episode 4 - abstract chalkboard background with colorful network nodes and circular icons Event Microsoft Research Forum | Episode 4 

    Leading researchers at Microsoft shared the latest multimodal AI models, advanced benchmarks for AI evaluation and model self-improvement, and an entirely new kind of computer for AI inference and hard optimization.

Data Formulator: Exploring how AI can help analysts create rich data visualizations

White icons representing AI and human computer interaction on a blue to purple to pink gradient.

Data Formulator’s architecture separates data transformation from chart configuration, improving both the user experience and AI performance. Refining how users interact with AI-powered tools is essential for improving how they communicate their requirements, paving the way for more efficient and effective collaboration.

  • News AI Dreams: Microsoft @ 50, Chapter 1 

    Since the early 1990s, the promise of AI has been a driving force at Microsoft Research, which has a track record of breakthroughs that continue to advance the state of the art.

Microsoft establishes a new lab, Microsoft Research Asia – Tokyo (opens in new tab)

Microsoft establishes a new lab, Microsoft Research Asia – Tokyo

The Tokyo lab will focus on critical areas that reflect Japan’s socioeconomic priorities, including embodied AI, well-being and neuroscience, societal AI, and industry innovation. These research efforts aim to leverage advanced technologies to foster societal progress and contribute to the region’s innovation ecosystem.

  • Outlined illustrations of Chris Hawblitzel and Jay Lorch for the Microsoft Research Podcast, Abstracts series. Podcast Verus: A Practical Foundation for Systems Verification 

    Researchers Chris Hawblitzel and Jay Lorch share how progress in programming languages and verification approaches are bringing bug-free software within reach. Their work on the Rust verification tool Verus won the Distinguished Artifact Award at SOSP ’24.

  • Outlined illustrations of Karin Strauss, Jake Smith, Bichlien Nguyen, and Sergey Yekhanin for the Microsoft Research Podcast, Ideas series. Podcast Ideas: The journey to DNA data storage 

    Research manager Karin Strauss and members of the DNA Data Storage Project reflect on the path to developing a synthetic DNA–based system for archival data storage, including the recent open-source release of its most powerful algorithm for DNA error correction.

MarS: A unified financial market simulation engine in the era of generative foundation models

MarS illustration with document workflow and chatbot icons on a purple gradient background

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.

Thank you for reading, watching, and listening

In 2024, contributions across the research community at Microsoft continued to advance the company’s vision of what technology can and should be: a means for empowering every person and every organization on the planet to achieve more.

To stay informed of the latest innovations, subscribe to the Microsoft Research Newsletter (opens in new tab) and the Microsoft Research Podcast (opens in new tab). You can also follow us on Bluesky (opens in new tab), Facebook (opens in new tab), Instagram (opens in new tab), LinkedIn (opens in new tab), X (opens in new tab), and YouTube (opens in new tab). 

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