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Tuesday, December 27, 2022

Microsoft Research Looks Back at Progress in AI

 Microsoft talks about some of its efforts. 

Research @ Microsoft 2022: A look back at a year of accelerating progress in AI

Published December 19, 2022

2022 has seen remarkable progress in foundational technologies that have helped to advance human knowledge and create new possibilities to address some of society’s most challenging problems. Significant advances in AI have also enabled Microsoft to bring new capabilities to customers through our products and services, including GitHub Copilot, an AI pair programmer capable of turning natural language prompts into code, and a preview of Microsoft Designer, a graphic design app that supports the creation of social media posts, invitations, posters, and one-of-a-kind images.

These offerings provide an early glimpse of how new AI capabilities, such as large language models, can enable people to interact with machines in increasingly powerful ways. They build on a significant, long-term commitment to fundamental research in computing and across the sciences, and the research community at Microsoft plays an integral role in advancing the state of the art in AI, while working closely with engineering teams and other partners to transform that progress into tangible benefits.

In 2022, Microsoft Research established AI4Science, a global organization applying the latest advances in AI and machine learning toward fundamentally transforming science; added to and expanded the capabilities of the company’s family of foundation models; worked to make these models and technologies more adaptable, collaborative, and efficient; further developed approaches to ensure that AI is used responsibly and in alignment with human needs; and pursued different approaches to AI, such as causal machine learning and reinforcement learning.

We shared our advances across AI and many other disciplines during our second annual Microsoft Research Summit, where members of our research community gathered virtually with their counterparts across industry and academia to discuss how emerging technologies are being explored and deployed to bring the greatest possible benefits to humanity.  

Plenary sessions at the event focused on the transformational impact of deep learning on the way we practice science, research that empowers medical practitioners and reduces inequities in healthcare, and emerging foundations for planet-scale computing. Further tracks and sessions over three days provided deeper dives into the future of the cloud; efficient large-scale AI; amplifying human productivity and creativity; delivering precision healthcare; building user trust through privacy, identity, and responsible AI; and enabling a resilient and sustainable world.


Microsoft Climate Research Initiative (MCRI) 

In June, the Microsoft Climate Research Initiative (MCRI) announced its first phase of collaborations among multidisciplinary researchers working together to accelerate cutting-edge research and transformative innovation in climate science and technology.


New Future of Work Report 2022 

In May, researchers across Microsoft published the New Future of Work Report 2022, which summarizes important recent research developments related to hybrid work. It highlights themes that have emerged in the findings of the past year and resurfaces older research that has become newly relevant.

In this blog post, we look back at some of the key achievements and notable work in AI and highlight other advances across our diverse, multidisciplinary, and global organization.

Advancing AI foundations and accelerating progress

Over the past year, the research community at Microsoft made significant contributions to the rapidly evolving landscape of powerful large-scale AI models. Microsoft Research and the Microsoft Turing team unveiled a new Turing Universal Language Representation model capable of performing both English and multilingual understanding tasks. In computer vision, advancements for the Project Florence-VL (Florence-Vision and Language) team spanned still imagery and video: its GIT model was the first to surpass human performance on the image captioning benchmark TextCaps; LAVENDER showed strong performance in video question answering, text-to-video retrieval, and video captioning; and GLIP and GLIPv2 combined localization and vision-language understanding. The group also introduced NUWA-Infinity, a model capable of converting text, images, and video into high-resolution images or long-duration video. Meanwhile, the Visual Computing Group scaled up its Transformer-based general-purpose computer vision architecture, Swin Transformer, achieving applicability across more vision tasks than ever before.   .... ' 

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