Microsoft Research Podcast

Senior Researcher Chang Liu discusses M-OFDFT, a variation of orbital-free density functional theory (OFDFT) that leverages deep learning to help identify molecular properties in a way that minimizes the tradeoff between accuracy and efficiency. Read the paper

Can how we think about our thinking help us better incorporate generative AI in our lives & work? Explore metacognition’s potential to improve the tech’s usability on “Abstracts,” then sign up for Microsoft Research Forum for more on this & other AI work.Read the paper

Partner Research Manager and developer experience expert Nicole Forsgren talks about the future of software engineering with AI, why she loves tech, and her reliance on a spreadsheet and her gut when making career-changing decisions.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

Partner Software Architect Ivan Tashev talks about applying his expertise in audio signal processing to the design and study of audio components for Microsoft products such as Kinect and shares how a focus on what he can control has fueled professional success.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 

On “Abstracts,” Jordan Ash & Dipendra Misra discuss the parameter reduction method LASER. Tune in to learn how selective removal of stored data alone can boost LLM performance, then sign up for Microsoft Research Forum for more on LASER & related topics.Learn more:The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction | Publication, December 2023LASER code on GitHub

Ashley Llorens hosts Chris Bishop to discuss the state of deep learning, their new textbook on the subject, and the potential for 'super copilots' in scientific breakthroughs. They explore advancements in deep learning, including pre-training and zero-shot learning, and highlight the applications of AI in healthcare and materials, such as molecule design and sustainable energy solutions.

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