Microsoft at ICML 2024: Innovations in machine learning

In an era increasingly steered by data, machine learning is a pivotal force, transforming vast amounts of information into actionable intelligence with unprecedented speed and accuracy. For example, recent advances in machine learning have led to breakthroughs in precision health, helping doctors make more informed decisions about patient care. Similarly, in climate science, machine learning is improving scientists’ ability to predict and mitigate the impact of extreme weather events. These innovations illustrate that machine learning not only streamlines workflows, it […]

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Abstracts: July 18, 2024

MITRA: So the post-training phase is very important for language models. You can really improve the model a lot by creating high-quality synthetic data. The problem is, however, though, high-quality synthetic data creation requires lots of human effort and expertise. The problem that we’re trying to tackle is, how do you reduce human effort? How can you create high-quality data with really low amount of human effort? When you have a language model and, let’s say, you want to apply […]

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Research Focus: Week of July 15, 2024

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 MG-TSD: Advancing time series analysis with multi-granularity guided diffusion model Diffusion probabilistic models have the capacity to generate high-fidelity samples for generative time series forecasting. However, they also present issues of instability due to their stochastic nature. In a recent article: MG-TSD: Advancing time series analysis with multi-granularity  

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Data-driven model improves accuracy in predicting EV battery degradation

Rising carbon emissions have significantly challenged sustainable development in recent years, prompting global efforts to implement carbon reduction policies and achieve long-term carbon neutrality. A crucial step in this transition involves the recycling and reuse of power batteries, which are assessed for their state-of-health (SoH) and then repaired or restructured for reuse in smaller-sized electric vehicles (EVs), energy storage systems, and smart streetlights. This process not only extends battery life but also maximizes their residual value. However, accurately assessing this […]

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RUBICON: Evaluating conversations between humans and AI systems

This paper has been accepted at the 1st ACM International Conference on AI-powered Software (opens in new tab) (AIware 2024), co-located with FSE 2024 (opens in new tab). AIware is the premier international forum on AI-powered software. Generative AI has redefined the landscape of AI assistants in software development, with innovations like GitHub Copilot providing real-time, chat-based programming support. As these tools increase in sophistication and domain specialization, assessing their impact  

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Unified Database: Laying the foundation for large language model vertical applications

Large language models (LLMs) have become a valuable technology in areas such as content creation, language comprehension, and intelligent dialogue, or interactions between people and computer systems. However, these models generate responses based on patterns and rules observed in fixed training data, which can potentially lead them to produce erroneous and even fictitious information. The models can also struggle with real-time knowledge updates. One technique known as retrieval augmented generation (RAG) can organically combine fresh external information  

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Empowering NGOs with generative AI in the fight against human trafficking

Human trafficking and labor exploitation are ancient problems that have evolved with each major leap in technology, from the agricultural revolution to the information age. But what if the right combination of people, data, and technology could help to tackle these problems on an unprecedented scale? With the emergence of generative AI models, which can create rich text and media from natural language prompts and real-world understanding, we are seeing new opportunities to advance the work of organizations that are […]

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GraphRAG: New tool for complex data discovery now on GitHub

Earlier this year, we introduced GraphRAG (opens in new tab), a graph-based approach to retrieval-augmented generation (RAG) that enables question-answering over private or previously unseen datasets. Today, we’re pleased to announce that GraphRAG is now available on GitHub (opens in new tab), offering more structured information retrieval and comprehensive response generation than naive RAG approaches. The GraphRAG code repository is complemented by a solution accelerator (opens in new tab), providing an easy-to-use  

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Research Focus: Week of June 24, 2024

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 Towards Energy Efficient 5G vRAN Servers Virtualized radio access networks (vRANs), which run the cellular radio stack on commodity servers instead of specialized hardware, are increasingly used in modern cellular networks (e.g., 5G), owing to advantages such as a multi-vendor ecosystem, easier maintenance, and faster feature upgrades. In a recent  

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Synergizing habits and goals with variational Bayes: A new framework for biological and artificial embodied agents

In the intertwined worlds of psychology, cognitive neuroscience, and artificial intelligence, scientists continue to pursue the elusive goal of decoding and mimicking human and animal behavior. One of the most intriguing aspects of this research is the interplay between two types of behaviors: habitual and goal directed. Traditionally, these behaviors are believed  

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