Episodes
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Episodes manquant?
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Innovative AI research often depends on access to resources. Microsoft wants to help. Technical Advisor Evelyne Viegas and distinguished faculty from two Minority Serving Institutions discuss the benefits of Microsoft’s Accelerating Foundation Models Research program in their lives and research.
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Host Peter Lee, Microsoft Research president, discusses the motivation behind the new series and the GPT-4 encounter that helped him view the tech not only as a potential tool for improving healthcare but a chance to reexamine what it means to care for people.
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Microsoft announced the creation of the first topoconductor and first QPU architecture with a topological core. Dr. Chetan Nayak, a technical fellow of Quantum Hardware at the company, discusses how the breakthroughs are redefining the field of quantum computing.
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In this episode, guest host Chris Stetkiewicz talks with Microsoft Principal Researcher Akshay Nambi about his focus on developing AI-driven technology that addresses real-world challenges at scale. Drawing on firsthand experiences, Nambi combines his expertise in electronics and computer science to create systems that enhance road safety, agriculture, and energy infrastructure. He’s currently working on AI-powered tools to improve education, including a digital assistant that can help teachers work more efficiently and create effective lesson plans and solutions to help improve the accuracy of models underpinning AI tutors.
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Struggles with programming languages helped research manager Shan Lu find her calling as a bug hunter. She discusses one bug that really haunted her, the thousands she’s identified since, and how she’s turning to LLMs to help make software more reliable.
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How do you generate and test materials that don’t exist yet? Researchers Tian Xie and Ziheng Lu share the story behind MatterGen and MatterSim, AI tools poised to transform materials discovery and help drive advances in energy, manufacturing, and sustainability.
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As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including Daepp and Ness’s research into the tech’s use in Taiwan and India.
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Just after his NeurIPS 2024 keynote on the co-evolution of systems and AI, Microsoft CVP Lidong Zhou joins the podcast to discuss how rapidly advancing AI impacts the systems supporting it and the opportunities to use AI to enhance systems engineering itself.
Learn more:
Verus: A Practical Foundation for Systems Verification | Publication, November 2024
SuperBench: Improving Cloud AI Infrastructure Reliability with Proactive Validation | Publication, July 2024
BitNet: Scaling 1-bit Transformers for Large Language Models | Publication, October 2023
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In this special edition of the podcast, Technical Fellow and Microsoft Research AI for Science Director Chris Bishop joins guest host Eliza Strickland in the Microsoft Booth at the 38th annual Conference on Neural Information Processing Systems (NeurIPS) in Vancouver, British Columbia, to talk about deep learning’s potential to improve the speed and scale at which scientific advancements can be made.
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Researcher Jindong Wang and Associate Professor Steven Euijong Whang explore the NeurIPS 2024 work ERBench. ERBench leverages relational databases to create LLM benchmarks that can verify model rationale via keywords in addition to checking answer correctness.
Read the paper
Get datasets and codes
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Next-token prediction trains a language model on all tokens in a sequence. VP Weizhu Chen discusses his team’s 2024 NeurIPS paper on how distinguishing between useful and “noisy” tokens in pretraining can improve token efficiency and model performance.
Read the paper
Get the code
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Can existing algorithms designed for simple reinforcement learning problems be used to solve more complex RL problems? Researcher Dylan Foster discusses the modular approach he and his coauthors explored in their 2024 NeurIPS paper on RL under latent dynamics.
Read the paper
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Pranjal Chitale discusses the 2024 NeurIPS work CVQA. Spanning 31 languages and the cultures of 30 countries, this VQA benchmark was created with native speakers and cultural experts to evaluate model performance across diverse linguistic and cultural contexts.
Read the paper
Get the dataset
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When Senior Principal Research Manager Nicole Immorlica discovered she could use math to make the world a better place for people, she was all in. She discusses working in computer science theory and economics, including studying the impact of algorithms and AI on markets.
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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.
Get the Trellis BMA code: GitHub - microsoft/TrellisBMA: Trellis BMA: coded trace reconstruction on IDS channels for DNA storage
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The efficient simulation of molecules has the potential to change how the world understands biological systems and designs new drugs and biomaterials. Tong Wang discusses AI2BMD, an AI-based system designed to simulate large biomolecules with speed and accuracy.
Read the paper
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