Microsoft Research Podcast

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 paper
• UniversalNER project website with demo
• Code on GitHub
• Dataset 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 2023
• AutoGen: 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 2023
• AI Explainer: Foundation models ​and the next era of AI, March 2023 
• AI and Microsoft Research

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 Anunay Kulshrestha and Karan Newatia talk to Senior Cryptographer Josh Benaloh about their work this summer on ElectionGuard, a free, open-source toolkit that enables voters to verify that their votes have been accurately counted. Kulshrestha and Newatia discuss their contributions to extending ElectionGuard to mail-in voting and rank-choice voting, respectively; what is needed for widespread adoption of the verifiable election technology; and why they’d recommend a Microsoft internship to other students.

(Editor’s note: After its design and development by Microsoft, ElectionGuard is now part of the newly formed nonprofit Election Technology Initiative, which will join with Microsoft to further ElectionGuard’s growth and help advance its adoption.)

Learn more

• ElectionGuard | Project page
• The next frontier in elections: Microsoft supports the Council of State Governments’ Election Technology Initiative | Microsoft On the Issues blog, July 2023
• Security and Cryptography | Group page

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 Sriram Rajamani, Distinguished Scientist and Managing Director of Microsoft Research India. Rajamani talks about how the lab’s work is being influenced by today’s rapidly advancing AI. One example? The development of a conversational agent in India capable of providing information about governmental agricultural programs in farmers’ natural language, particularly significant in a country with more than 30 languages, including 22 government-recognized languages. It’s an application Microsoft CEO Satya Nadella described as the “mic drop moment” of his trip to the lab early this year.

Learn more

• AI4Bhārat | Organization homepage
• MEGA: Multilingual Evaluation of Generative AI | Publication, May 2023
• AI and Microsoft Research | Learn more about the breadth of AI research at Microsoft

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 new 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 talks with Microsoft Health Futures Senior Director Javier Alvarez and Dr. Raj Jena, a radiation oncologist at Addenbrooke’s hospital, part of Cambridge University Hospitals in the United Kingdom, about Project InnerEye, a Microsoft Research effort that applies machine learning to medical image analysis. The pair shares how a 10-plus-year collaborative journey—and a combination of research and good software engineering—has resulted in the hospital’s creation of an AI system that is helping to decrease the time cancer patients have to wait to begin treatment. Alvarez and Jena chart the path of their collaboration in AI-assisted medical imaging, from Microsoft Research’s initiation of Project InnerEye and its decision to make the resulting research tools available in open source to Addenbrooke’s subsequent testing and validation of these tools to meet the regulatory requirements for use in a clinical setting. They also discuss supporting clinician productivity—and ultimately patient outcomes—and the important role patients play in incorporating AI into healthcare.

Learn more:

• Project InnerEye | Project page
• How AI is helping to shrink waiting times for NHS cancer patients | Microsoft News Centre UK blog post, June 2023
• Accounting for past imaging studies: Enhancing radiology AI and reporting | Microsoft Research blog, June 2023
• Microsoft Health Futures | Lab page
• Biomedical Imaging | Research group page
• Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers | JAMA publication, November 2020

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 new 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 of the podcast, Dr. Gretchen Huizinga welcomes Principal Researcher Dr. Jina Suh and Principal Applied and Data Science Manager Dr. Shamsi Iqbal to the show to discuss their most recent work together, a research project aimed at developing data-driven tools to support organizational leaders and executives in their decision-making. The longtime collaborators explore how a long history of collaboration helps them thrive in their work to help workplaces thrive, how their relationship has evolved over the years, particularly with Iqbal’s move from the research side to the product side, and how research and product can align to achieve impact.

Learn more:

• HUE: Human Understanding and Empathy | Project page
• Microsoft Viva | Product page