Microsoft Research Podcast

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 | Publication, July 2020Project VeLLM | Project pageKahani: Visual Storytelling | Project pageKahani: Visual Storytelling through Culturally Nuanced Images | Microsoft Research Forum | Episode 1, January 2024Teachers in India help Microsoft Research design AI tool for creating great classroom content | Microsoft Research blog, October 2023Digital Labor: Project Karya | Project pageVillage by village, creating the building blocks for AI tools with work that also educates | Microsoft Source Asia blog, February 2024

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 | Focus AreaEvaluating Cognitive Maps and Planning in Large Language Models with CogEval | Publication, October 2023Imitating Human Behaviour with Diffusion Models | Publication, May 2023Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games | Publication, April 2023Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation | Publication, July 2021Predictive Representations in Hippocampal and Prefrontal Hierarchies | Publication, January 2022The successor representation in human reinforcement learning | Publication, September 2017Encoding of Prospective Tasks in the Human Prefrontal Cortex under Varying Task Loads | Publication, October 2013

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.” 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

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 Behavioral Science Researcher Lev Tankelevitch joins host Gretchen Huizinga to discuss “The Metacognitive Demands and Opportunities of Generative AI.” In their paper, Tankelevitch and his coauthors propose using the scientific study of how people monitor, understand, and adapt their thinking to address common challenges of incorporating generative AI into life and work—from crafting effective prompts to determining the value of AI-generated outputs. To learn more about the paper and related topics, register for Microsoft Research Forum, a series of panel discussions and lightning talks around science and technology research in the era of general AI.Read the paper

In the Microsoft Research Podcast series What’s Your Story, Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. A systems expert whose 10 years with Microsoft spans research and product, Gehrke talks to members of the company’s research community about what motivates their work and how they got where they are today.Partner Research Manager and leading developer experience expert Nicole Forsgren oversees Microsoft Research efforts to enhance software engineering effectiveness through the study of developer productivity, community, and well-being. In this episode, she discusses AI’s potential impact on software engineering, what she loves about tech, and how thoughtful decision making—combined with listening to her gut—has led to opportunities as a developer, accounting professor, and founder and CEO of a startup that was eventually acquired by Google.Learn more:Nicole Forsgren at Microsoft ResearchNicole Forsgren websiteQuantifying the impact of developer experience | Microsoft Azure Blog, January 2024Yes, good DevEx increases productivity. Here is the data. | GitHub blog, January 2024Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations | Book, 2018

In the Microsoft Research Podcast series What’s Your Story, Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. A systems expert whose 10 years with Microsoft spans research and product, Gehrke talks to members of the company’s research community about what motivates their work and how they got where they are today.Partner Software Architect Ivan Tashev’s expertise in audio signal processing has contributed to the design and study of audio components for Microsoft products such as Kinect, Teams, and HoloLens. In this episode, Tashev discusses how a first-place finish in the Mathematical Olympiad fueled a lifelong passion for shooting film; how a company event showcasing cutting-edge projects precipitated his move from product back to research; and how laser focus on things within his control has helped him find success in 25-plus years with Microsoft.Learn more:Ivan Tashev at Microsoft ResearchDistributed Meetings: A Meeting Capture and Broadcasting System | Publication, December 2002Research Collection: The Unseen History of Audio and Acoustics Research at Microsoft | Microsoft Research blog, August 2020 

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 Researchers Jordan Ash and Dipendra Misra join host Gretchen Huizinga to discuss “The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction,” which was accepted to the 2024 International Conference on Learning Representations (ICLR). Layer-Selective Rank reduction, or LASER, is an intervention for targeted parameter reduction in transformer-based models. The work shows that the removal of certain parameters not only maintains model performance like some existing parameter-reduction methods but can actually improve it—no additional training necessary.To learn more about the paper and related topics, register for Microsoft Research Forum, a series of panel discussions and lightning talks around science and technology research in the era of general AI.Learn more:The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction | Publication, December 2023LASER code on GitHub

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 healthcare and education, and its potential to benefit humanity.This episode features Technical Fellow Christopher Bishop, who leads a global team of researchers and engineers working to help accelerate scientific discovery by merging machine learning and the natural sciences. Llorens and Bishop explore the state of deep learning; Bishop’s new textbook Deep Learning: Foundations and Concepts, his third and a writing collaboration with his son; and a potential future in which “super copilots” accessible via natural language and drawing on a variety of tools, like those that can simulate the fundamental equations of nature, are empowering scientists in their pursuit of breakthrough.Learn more:Deep Learning: Foundations and Concepts | Textbook, 2023Pattern Recognition and Machine Learning | Textbook, 2006Neural Networks for Pattern Recognition | Textbook, 1995

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 Principal Research Manager Tao Qin and Senior Researcher Lijun Wu discuss “FABind: Fast and Accurate Protein-Ligand Binding.” The paper, accepted at the 2023 Conference on Neural Information Processing Systems (NeurIPS), introduces a new method for predicting the binding structures of proteins and ligands during drug development. The method demonstrates improved speed and accuracy over current methods.Learn more:FABind: Fast and Accurate Protein-Ligand BindingFABind code on GitHub

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, Principal Researcher Alessandro Sordoni joins host Gretchen Huizinga to discuss “Joint Prompt Optimization of Stacked LLMs using Variational Inference.” In the paper, which was accepted at the 2023 Conference on Neural Information Processing Systems (NeurIPS), Sordoni and his coauthors introduce Deep Language Networks, or DLNs, an architecture that treats large language models as layers within a network and natural language prompts as each layer’s learnable parameters.Read the paper

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, Xing Xie, a Senior Principal Research Manager of Microsoft Research Asia, joins host Dr. Gretchen Huizinga to discuss “Evaluating General-Purpose AI with Psychometrics.” As AI capabilities move from task specific to more general purpose, the paper explores psychometrics, a subfield of psychology, as an alternative to traditional methods for evaluating model performance and for supporting consistent and reliable systems.Read the paper: Evaluating General-Purpose AI with Psychometrics

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.In this episode, Dr. Gretchen Huizinga speaks with Cecily Morrison, MBE, a Senior Principal Research Manager at Microsoft Research, and Karolina Pakėnaitė, who also goes by Caroline, a PhD student and member of the citizen design team working with Morrison on the research project Find My Things. An AI phone application designed to help people who are blind or have low vision locate their personal items, Find My Things is an example of a broader research approach known as Teachable AI. Morrison and Pakėnaitė explore the Teachable AI goal of empowering people to make an AI experience work for them. They also discuss how “designing for one” when it comes to inclusive design leads to innovative solutions and what they learned about optimizing these types of systems for real-world use (spoiler: it’s not necessarily more or higher-quality data).Learn more:Teachable AI Experiences (Tai X) | Project pageUnderstanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision | Publication, October 2023Microsoft Inclusive Design | Inclusive design resource centerDeafBlind Everest Project | Karolina (Caroline) Pakėnaitė personal website

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, Shrey Jain, a Technical Project Manager at Microsoft Research, and Dr. Zoë Hitzig, a junior fellow at the Harvard Society of Fellows, discuss their work on contextual confidence, which presents a framework to understand and more meaningfully address the increasingly sophisticated challenges generative AI poses to communication.Read the paper

In this new Microsoft Research Podcast series What’s Your Story, Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. A systems expert whose 10 years with Microsoft spans research and product, Gehrke talks to members of the company’s research community about what motivates their work and how they got where they are today.Across his time at Microsoft, Desney Tan, Managing Director of Microsoft Research Redmond, has had the experience of shepherding research ideas into products multiple times, and much like the trajectory of research, his life journey has been far from linear. In this episode, Tan shares how he moved to the United States from Singapore as a teenager, how his self-described “brashness” as a Microsoft intern helped shift the course of his career, and how human impact has been a guiding force in his work.

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, Andy Gordon, a Partner Research Manager, and Carina Negreanu, a Senior Researcher, both at Microsoft Research, join host Dr. Gretchen Huizinga to discuss “Co-audit: Tools to help humans double-check AI-generated content.” This paper brings together current understanding of generative AI performance to explore the need and context for tools to help people using the technology find and fix mistakes in AI output.View the paper

In this new Microsoft Research Podcast series What’s Your Story, Lab Director Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. He talks to members of the research community at Microsoft about what motivates their work and how they got where they are today.Ranveer Chandra is Managing Director of Research for Industry and CTO of Agri-Food. He is also Head of Networking Research at Microsoft Research Redmond. His work in systems and networking is helping to bring more internet connectivity to more people and is yielding tools designed to help farmers increase food production more affordably and sustainably. In this episode, he shares what it was like growing up in Jamshedpur, India; why he focuses his efforts in the areas he does; and where the joy in his work comes from.Learn more:Ranveer Chandra at Microsoft ResearchFarmBeats: AI, Edge & IoT for AgricultureProject FarmVibes6G | Space

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, Dr. Sheng Zhang, a Senior Researcher at Microsoft Research, joins host Dr. Gretchen Huizinga to discuss “UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition.” In this paper, Zhang and his coauthors present mission-focused instruction tuning, a method for distilling large language models into smaller, more efficient ones for a broad application class. Their UniversalNER models achieved state-of-the-art performance in named entity recognition, an important natural language processing (NLP) task. Model distillation has the potential to make NLP and other capabilities more accessible, particularly in specialized domains such as biomedicine, which could benefit from more resource-efficient and transparent options. Learn more:View the paperUniversalNER project website with demoCode on GitHubDataset and models on Hugging Face

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, PhD students Jennifer Scurrell and Alejandro Cuevas talk to Senior Researcher Dr. Madeleine Daepp. They discuss the internship culture at Microsoft Research, from opportunities to connect with researchers they admire over coffee to the teamwork they say helped make it possible for them to succeed in the fast-paced environment of industry, and the impact they hope to have with their work. Learn more:Automated Interviewer or Augmented Survey? Collecting Social Data with Large Language Models | Publication, September 2023 

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 healthcare and education, and its potential to benefit humanity.This episode features Partner Research Manager Hanna Wallach, whose research into fairness, accountability, transparency, and ethics in AI and machine learning has helped inform the use of AI in Microsoft products and services for years. Wallach describes how she and a team of applied scientists expanded their tools for measuring fairness-related harms in AI systems to address harmful content more broadly during their involvement in the deployment of Bing Chat; her interest in filtering, a technique for mitigating harms that she describes as widely used but not often talked about; and the cross-company collaboration that brings policy, engineering, and research together to evolve and execute the Microsoft approach to developing and deploying AI responsibly.Learn more: Microsoft AI: Responsible AI Principles and Approach  AI and Microsoft Research 

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 healthcare and education, and its potential to benefit humanity.This episode features Senior Principal Research Manager Ahmed H. Awadallah, whose work improving the efficiency of large-scale AI models and efforts to help move advancements in the space from research to practice have put him at the forefront of this new era of AI. Awadallah discusses the shift in dynamics between model size and amount—and quality—of data when it comes to model training; the recently published paper “Orca: Progressive Learning from Complex Explanation Traces of GPT-4,” which further explores the use of large-scale AI models to improve the performance of smaller, less powerful ones; and the need for better evaluation strategies, particularly as we move into a future in which Awadallah hopes to see gains in these models’ ability to continually learn.Learn more:Orca: Progressive Learning from Complex Explanation Traces of GPT-4, June 2023 Textbooks Are All You Need II: phi-1.5 technical report, September 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework, August 2023 LIDA: Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models, March 2023AI Explainer: Foundation models ​and the next era of AI, March 2023 AI and Microsoft Research