Episodios
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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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¿Faltan episodios?
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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
Get the code
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Researcher Siddharth Suri and professor David Holtz give a brief history of prompt engineering, discuss the debate behind their recent collaboration, and share what they found from studying how people’s approaches to prompting change as models advance.
Learn more:
As Generative Models Improve, People Adapt Their Prompts | Publication, July 2024AI, Cognition, and the Economy (AICE) | Initiative page -
Researchers Chris Hawblitzel and Jay Lorch share how progress in programming languages and verification approaches are bringing bug-free software within reach. Their work on the Rust verification tool Verus won the Distinguished Artifact Award at SOSP ’24.
Read the paper
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In their 2024 SOSP paper, researchers explore a common—though often undertested—software system issue: retry bugs. Research manager Shan Lu and PhD candidate Bogdan Stoica share how they’re combining traditional program analysis and LLMs to address the challenge.
Read the paper
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Every year, interns from academic institutions around the world apply and grow their knowledge as members of the research community at Microsoft. In this Microsoft Research Podcast series, these students join their internship supervisors to share their experience working alongside some of the leading researchers in their respective fields.
In this episode, Angela Busheska, an undergraduate engineering student at Lafayette College, talks to Senior Researcher Vaishnavi Ranganathan, about her work on TerraTrace, a platform that brings together statistics and large language models to track land use over time for agricultural and forestry applications. Busheska discusses the personal loss that drew her to climate activism, the chain of events that led to a memorable face-to-face meeting with Microsoft’s chief sustainability officer, and her advice for going after the internship you want and making the experience count.
Learn more:
TerraTrace | GitHub repoProject FarmVibes | Project homepageProject FoodVibes | Project homepage -
The personalizable object recognizer Find My Things was recently recognized for accessible design. Researcher Daniela Massiceti and software development engineer Martin Grayson talk about the research project’s origins and the tech advances making it possible.
The Find My Things story is an example of research at Microsoft enhancing Microsoft products and services. To try the Find My Things tool, download the free, publicly available Seeing AI app.
Learn more:
Find My Things: Personalized Accessibility through Teachable AI for People who are Blind or Low Vision | Publication, May 2024Understanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision | Publication, October 2023Teachable AI Experiences (Tai X) | Project pagePeopleLens | Publication, June 2021ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition | Publication, October 2021Collaborators: Teachable AI with Cecily Morrison and Karolina Pakėnaitė | Microsoft Research Podcast, December 2023 -
College freshman Dexter Greene and Microsoft research manager Richard Black discuss how technology that stores data in glass is supporting students as they expand earlier efforts to communicate what it means to be human to extraterrestrials.
Learn more:
Avenues: The World School — Golden Record 2.0Project homepageGolden Record: OverviewNASA ScienceProject SilicaProject homepageSealed in glassMicrosoft Unlocked innovation story, 2023Optics for the cloud: storage in the zettabyte era with Dr. Ant Rowstron and Mark RussinovichMicrosoft Research Podcast, November 2019Project Silica proof of concept stores Warner Bros. ‘Superman’ movie on quartz glassMicrosoft Source blog, November 2019 -
Model maker and fabricator Lex Story helps bring research to life through prototyping. He discusses his take on failure; the encouragement and advice that has supported his pursuit of art and science; and the sabbatical that might inspire his next career move.
Learn more:
Microsoft PremonitionProject EclipseProject PRISM3D TelemedicineJacdacAudio Devices -
In this episode, Microsoft Product Manager Shrey Jain and OpenAI Research Scientist Zoë Hitzig join host Amber Tingle to discuss “Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online.” In their paper, Jain, Hitzig, and their coauthors describe how malicious actors can draw on increasingly advanced AI tools to carry out deception, making online deception harder to detect and more harmful. Bringing ideas from cryptography into AI policy conversations, they identify a possible mitigation: a credential that allows its holder to prove they’re a person––not a bot––without sharing any identifying information. This exploratory research reflects a broad range of collaborators from across industry, academia, and the civil sector specializing in areas such as security, digital identity, advocacy, and policy.
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Researcher Brendan Lucier and professor Mert Demirer are applying their micro- and macroeconomic expertise, respectively, to forecasting the economic impact of AI. They share how they’re using a task-level breakdown of occupations to help predict the future.
Learn more:
AI, Cognition, and the Economy (AICE) | Initiative pageIdeas: Designing AI for people with Abigail Sellen | Microsoft Research Podcast, May 2024 -
Emre Kiciman shares how some keen observations and a desire to have front-end impact led him to make the jump from systems and networking to computational social science and now causal analysis and large-scale AI—and how systems thinking still impacts his work.
Learn more:
AI Controller Interface: Generative AI with a lightweight, LLM-integrated VM (blog)AICI: Prompts as (Wasm) Programs (GitHub) - Mostrar más
