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Innhold levert av Researchers across the Microsoft research community. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Researchers across the Microsoft research community eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

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Understanding the Elegant Math Behind Modern Machine Learning 1:14:43

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1:14:43

Artificial intelligence is evolving at an unprecedented pace—what does that mean for the future of technology, venture capital, business, and even our understanding of ourselves? Award-winning journalist and writer Anil Ananthaswamy joins us for our latest episode to discuss his latest book Why Machines Learn: The Elegant Math Behind Modern AI . Anil helps us explore the journey and many breakthroughs that have propelled machine learning from simple perceptrons to the sophisticated algorithms shaping today’s AI revolution, powering GPT and other models. The discussion aims to demystify some of the underlying mathematical concepts that power modern machine learning, to help everyone grasp this technology impacting our lives–even if your last math class was in high school. Anil walks us through the power of scaling laws, the shift from training to inference optimization, and the debate among AI’s pioneers about the road to AGI—should we be concerned, or are we still missing key pieces of the puzzle? The conversation also delves into AI’s philosophical implications—could understanding how machines learn help us better understand ourselves? And what challenges remain before AI systems can truly operate with agency? If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform. Sign up for our newsletter at techsurgepodcast.com for exclusive insights and updates on upcoming TechSurge Live Summits. Links: Read Why Machines Learn, Anil’s latest book on the math behind AI https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Learn more about Anil Ananthaswamy’s work and writing https://anilananthaswamy.com/ Watch Anil Ananthaswamy’s TED Talk on AI and intelligence https://www.ted.com/speakers/anil_ananthaswamy Discover the MIT Knight Science Journalism Fellowship that shaped Anil’s AI research https://ksj.mit.edu/ Understand the Perceptron, the foundation of neural networks https://en.wikipedia.org/wiki/Perceptron Read about the Perceptron Convergence Theorem and its significance https://www.nature.com/articles/323533a0…

Microsoft Research Podcast

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An ongoing series of conversations bringing you right up to the cutting edge of Microsoft Research.

306 episoder

#Machine Learning #Tech #Researchers across the Microsoft research community

Microsoft Research Podcast

392 subscribers

updated for 5 dager siden

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An ongoing series of conversations bringing you right up to the cutting edge of Microsoft Research.

306 episoder

#Machine Learning #Tech #Researchers across the Microsoft research community

Alle episoder

Microsoft Research Podcast

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The AI Revolution in Medicine, Revisited: An Introduction 11:48

for 5 dager siden11:48

11:48

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.

Microsoft Research Podcast

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Ideas: Quantum computing redefined with Chetan Nayak 57:04

for 20 dager siden57:04

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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.

Microsoft Research Podcast

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Ideas: Building AI for population-scale systems with Akshay Nambi 25:41

for 28 dager siden25:41

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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.…

Microsoft Research Podcast

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Ideas: Bug hunting with Shan Lu 45:16

for 7 weeks siden45:16

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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.

Microsoft Research Podcast

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Ideas: AI for materials discovery with Tian Xie and Ziheng Lu 49:58

for 8 weeks siden49:58

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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.

Microsoft Research Podcast

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Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness 51:23

for 12 weeks siden51:23

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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.

Microsoft Research Podcast

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NeurIPS 2024: The co-evolution of AI and systems with Lidong Zhou 17:36

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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…

Microsoft Research Podcast

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NeurIPS 2024: AI for Science with Chris Bishop 21:49

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21:49

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.…

Microsoft Research Podcast

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Abstracts: NeurIPS 2024 with Jindong Wang and Steven Euijong Whang 11:34

for 13 weeks siden11:34

11:34

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

Microsoft Research Podcast

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Abstracts: NeurIPS 2024 with Weizhu Chen  8:27

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8:27

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

Microsoft Research Podcast

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Abstracts: NeurIPS 2024 with Pranjal Chitale 10:45

for 14 weeks siden10:45

10:45

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

Microsoft Research Podcast

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Abstracts: NeurIPS 2024 with Dylan Foster 10:42

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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

Microsoft Research Podcast

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Ideas: Economics and computation with Nicole Immorlica 36:15

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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.

Microsoft Research Podcast

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Ideas: The journey to DNA data storage 42:39

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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…

Microsoft Research Podcast

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Abstracts: November 14, 2024 13:30

for 17 weeks siden13:30

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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 Get the code

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