Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.In this episode, Senior Research Software Engineer Tusher Chakraborty joins host Gretchen Huizinga to discuss “Spectrumize: Spectrum-efficient Satellite Networks for the Internet of Things,” which was accepted at the 2024 USENIX Symposium on Networked Systems Design and Implementation (NSDI). In the paper, Chakraborty and his coauthors share their efforts to address the challenges of delivering reliable and affordable IoT connectivity via satellite-based networks. They propose a method for leveraging the motion of small satellites to facilitate efficient communication between a large IoT-satellite constellation and devices on Earth within a limited spectrum.Read the paper

Abstracts: April 16, 2024

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Behind every emerging technology is a great idea propelling it forward. In the new Microsoft Research Podcast series, Ideas, members of the research community at Microsoft discuss the beliefs that animate their research, the experiences and thinkers that inform it, and the positive human impact it targets. In this episode, host Gretchen Huizinga talks with Rafah Hosn, partner group product manager for AI Frontiers at Microsoft Research. Hosn’s professional experience spans the gamut—from research to product to engineering to research again, the discipline’s uniquely high levels of creativity, curiosity, and intellect drawing her back in. Energized by past technical disruptions she’s experienced, Hosn is on what she describes as her “most exciting adventure” yet, helping to drive scientific advancement in AI and to answer a big question: how far can we push machine intelligence while still delivering technologies people can derive value from? Learn more:* AI Frontiers - Microsoft Research (https://www.microsoft.com/en-us/research/lab/ai-frontiers/)* Responsible AI Principles and Approach | Microsoft AI (https://www.microsoft.com/en-us/ai/principles-and-approach/)

Ideas: Exploring AI frontiers with Rafah Hosn

Behind every emerging technology is a great idea propelling it forward. In the new Microsoft Research Podcast series, Ideas, members of the research community at Microsoft discuss the beliefs that animate their research, the experiences and thinkers that inform it, and the positive human impact it targets. In this episode, host Gretchen Huizinga talks with Principal Researcher Kalika Bali. Inspired by an early vision of “talking computers” and a subsequent career in linguistics, Bali has spent the last two decades bringing the two together. Aided by recent advances in large language models and motivated by her belief that everyone should have access to AI in their own language, Bali and her teams are building language technology applications that they hope will bring the benefits of generative AI to under-resourced and underserved language communities around the world.Learn more:* The State and Fate of Linguistic Diversity and Inclusion in the NLP World (https://www.microsoft.com/en-us/research/publication/the-state-and-fate-of-linguistic-diversity-and-inclusion-in-the-nlp-world/) | Publication, July 2020* Project VeLLM (https://www.microsoft.com/en-us/research/project/project-vellm/) | Project page* Kahani: Visual Storytelling (https://www.microsoft.com/en-us/research/project/kahani/) | Project page* Kahani: Visual Storytelling through Culturally Nuanced Images (https://www.microsoft.com/en-us/research/quarterly-brief/jan-2024-brief/articles/kahani-visual-storytelling-through-culturally-nuanced-images/) | Microsoft Research Forum | Episode 1, January 2024* Teachers in India help Microsoft Research design AI tool for creating great classroom content (https://www.microsoft.com/en-us/research/blog/teachers-in-india-help-microsoft-research-design-ai-tool-for-creating-great-classroom-content/) | Microsoft Research blog, October 2023* Digital Labor: Project Karya (https://www.microsoft.com/en-us/research/project/project-karya/) | Project page* Village by village, creating the building blocks for AI tools with work that also educates (https://news.microsoft.com/source/asia/features/village-by-village-creating-the-building-blocks-for-ai-tools-with-work-that-also-educates/) | Microsoft Source Asia blog, February 2024

Ideas: Language technologies for everyone with Kalika Bali

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.This episode features Principal Researcher Ida Momennejad. Momennejad is applying her expertise in cognitive neuroscience and computer science to better understand—and extend—AI capabilities, particularly when it comes to multistep reasoning and short- and long-term planning. Llorens and Momennejad discuss the notion of general intelligence in both humans and machines; how Momennejad and colleagues leveraged prior research into the cognition of people and rats to create prompts for evaluating large language models; and the case for the development of a “prefrontal cortex” for AI.Learn more:* AI and Microsoft Research (https://www.microsoft.com/en-us/research/focus-area/ai-and-microsoft-research/) | Focus Area* Evaluating Cognitive Maps and Planning in Large Language Models with CogEval (https://www.microsoft.com/en-us/research/publication/evaluating-cognitive-maps-in-large-language-models-with-cogeval-no-emergent-planning/) | Publication, October 2023* Imitating Human Behaviour with Diffusion Models (https://www.microsoft.com/en-us/research/publication/imitating-human-behaviour-with-diffusion-models/) | Publication, May 2023* Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games (https://www.microsoft.com/en-us/research/publication/navigates-like-me-understanding-how-people-evaluate-human-like-ai-in-video-games/) | Publication, April 2023* Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation (https://www.microsoft.com/en-us/research/publication/navigation-turing-test-ntt-learning-to-evaluate-human-like-navigation/) | Publication, July 2021* Predictive Representations in Hippocampal and Prefrontal Hierarchies (https://www.microsoft.com/en-us/research/publication/predictive-representations-in-hippocampal-and-prefrontal-hierarchies/) | Publication, January 2022* The successor representation in human reinforcement learning (https://www.microsoft.com/en-us/research/publication/the-successor-representation-in-human-reinforcement-learning/) | Publication, September 2017* Encoding of Prospective Tasks in the Human Prefrontal Cortex under Varying Task Loads (https://www.microsoft.com/en-us/research/publication/encoding-of-prospective-tasks-in-the-human-prefrontal-cortex-under-varying-task-loads/) | Publication, October 2013

AI Frontiers: Rethinking intelligence with Ashley Llorens and Ida Momennejad

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements. In this episode, Senior Researcher Chang Liu joins host Gretchen Huizinga to discuss Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning (https://www.microsoft.com/en-us/research/publication/overcoming-the-barrier-of-orbital-free-density-functional-theory-for-molecular-systems-using-deep-learning/).” In the paper, Liu and his coauthors present M-OFDFT, a variation of orbital-free density functional theory (OFDFT). M-OFDFT leverages deep learning to help identify molecular properties in a way that minimizes the tradeoff between accuracy and efficiency, work with the potential to benefit areas such as drug discovery and materials discovery.Read the paper

Abstracts: April 16, 2024

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