Distributional Graphormer, Microsoft’s new deep learning framework for predicting the equilibrium distribution of molecular structures, can generate realistic and diverse molecular structures with high efficiency and low cost.
Imagine an AI model that can seamlessly generate high-quality content across text, images, video, and audio, all at once. Such a model would more accurately capture the multimodal nature of the world and human comprehension, seamlessly consolidate information from a wide range of sources, and…
Picture a world where computing is not limited by the binary confines of zeros and ones, but instead, is free to explore the vast possibilities of continuous value data. Over the past three years a team of Microsoft researchers has been developing a new kind…
In this issue: Our new Responsible AI Maturity Model; FoundWright helps “re-find” web pages; Trace-guided Inductive Synthesis of Recursive Functional Programs; a wait-free algorithm for weak reference counting; and new research on concurrency testing.
Large AI models are transforming the digital world. Generative language models like Turing-NLG, ChatGPT, and GPT-4, powered by large language models (LLMs), are incredibly versatile, capable of performing tasks like summarization, coding, and translation. Similarly, large multimodal generative models like DALL·E, Microsoft Designer, and Bing…
In the vast realm of artificial intelligence, few fields have captivated our imagination and pushed the boundaries of possibility quite like computer vision. At the core of this domain of research and innovation lies the ambition to empower technologies for real-world vision-based systems, enabling machines…
This content was previously published by Nature Portfolio and Springer Nature Communities (opens in new tab) on Nature Portfolio Earth and Environment Community (opens in new tab). Improving our ability to forecast the weather and climate is of interest to all sectors of the economy and…
The use of self-supervision from image-text pairs has been a key enabler in the development of scalable and flexible vision-language AI models in not only general domains but also in biomedical domains such as radiology. The goal in the radiology setting is to produce rich…
In this issue: Peter Lee discusses AI in medicine. Plus, new research on data inference privacy in machine learning; PII leakage in language models; and automatic prompt organization with gradient descent and beam search.
Providing healthcare in remote or rural areas is challenging, particularly specialized medicine and surgical procedures. Patients may need to travel long distances just to get to medical facilities and to communicate with caregivers. They may not arrive in time to receive essential information before their…
In this edition: New research explores the causal ability of LLMs and DNA storage in thermoresponsive capsules; a talk on human-centered AI; and a CFP for funding for LLM productivity research projects from the Microsoft New Future of Work Initiative.
This research paper was accepted by the eighth ACM/IEEE Conference on Internet of Things Design and Implementation (opens in new tab) (IoTDI), which is a premier venue on IoT. The paper describes a framework that leverages cloud resources to execute large deep neural network (DNN) models…
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