Microsoft Research Forum (opens in new tab) is a new series of conversations that explore recent advances, bold new ideas, and important discussions within the global research community. Leading Microsoft researchers will share insights into their work, followed by live online discussions with audience participants.
This post provides an overview of the inaugural Microsoft Research Forum conversation, with a summary of each presentation. Full details, including the copilot experience (opens in new tab) and replays of each session (opens in new tab), are available on demand. Register now (opens in new tab) to attend upcoming Research Forum events.
Keynote: Research in the era of AI
Peter Lee, CVP, Microsoft Research & Incubations
2023 was an incredible year for AI research, with rapid change and the emerging sparks of artificial general intelligence. Generative AI now influences everything in research, and research has never mattered more to innovating technology that will benefit society. And while there is plenty of reason for optimism, we must also be clear-eyed about risks and limitations—another direction where research can play an important role.
In this environment, openness and collaboration are essential, not just to advance the research, but to ensure technology is developed with a commitment to safety and ethical use. Microsoft continues to invest in its commitment to responsible AI (RAI), which is deeply integrated not only into every engineering group across the company, but also across functions like finance, security, and legal teams. Additional progress will require close collaboration with the broader research community.
Some of the most promising and tangible advances are coming in medicine and materials science. Examples include work by Microsoft AI4Science, a Microsoft Research lab, which is working with the Global Health Drug Discovery Institute to accelerate discovery of new treatments for infectious diseases.
Panel discussion: AI Frontiers
Ashley Llorens, VP and Distinguished Scientist, Microsoft
Ece Kamar, Managing Director, Microsoft Research AI Frontiers
Sébastien Bubeck, VP, Microsoft GenAI
Ahmed Awadallah, Senior Principal Research Manager, Microsoft Research AI Frontiers
The panelists explored their aspirations for AI in the near future, as well as the challenges to overcome. Examples include:
- Going beyond language to build AI systems that become helpers in the physical world. AI can do more than just answer questions; it can better understand our goals and intentions and create a difference in people’s lives.
- Beyond trying to get AI to mimic the human mind, can AI actually illuminate how the human mind works and uncover the building blocks of reasoning?
- Making AI technology smaller would help reduce the cost and increase the performance of current AI systems. How can we divide problems into smaller pieces to solve? And how can we lower the requirements of big data, large neural networks, and massive computing resources?
- Can we create a virtuous feedback loop, where AI learns from people that use it, rather than simply delivering answers from a static base of information?
The panelists also explored the rapid pace of technology development. Historical timelines of three to five years are now condensed into mere weeks. In this environment, collaboration is essential to quickly develop ideas and scale up experimentation across organizations. This also amplifies existing concerns about optimizing for safety and alleviating bias in language models.
Lightning Talks
Improving reasoning in language models with LASER: Layer-Selective Rank Reduction
Dipendra Misra, Senior Researcher, Microsoft Research NYC and AI Frontiers
Large language models (LLMs) have revolutionized machine learning. As researchers continue to advance this technology, one approach involves performing an intervention in the models and observing how that affects their performance. This talk presents LASER, a new method of intervention that can increase LLMs’ accuracy while reducing their memory footprint.
Evaluation and understanding of foundation models
Besmira Nushi, Principal Researcher, Microsoft Research AI Frontiers
Model evaluation and understanding serve as guides to AI innovation. But evaluation is hard, and new generative tasks pose new challenges in evaluation and understanding. This talk explores efforts to measure, inform, and accelerate model improvement, which help the scientific community understand and study new forms and levels of intelligence.
Generative AI meets structural biology: Equilibrium distribution prediction
Shuxin Zheng, Principal Researcher, Microsoft Research AI4Science
Distributional Graphormer (DIG) is a deep learning framework for predicting protein structures with greater accuracy, a fundamental challenge in molecular science. Using generative AI to solve the problem of predicting equilibrium distribution, DIG opens exciting new possibilities. By learning about different states and behaviors of molecules, scientists can make breakthroughs in developing new drugs, creating advanced materials, and understanding biological processes.
Augmenting human cognition and decision making with AI
Jake Hofman, Senior Principal Researcher, Microsoft Research NYC
How can AI help people make better decisions, be more productive, and improve themselves in a sustainable way? Some technology can help in the short term without providing lasting solutions. For example, relying on a spell checker may not improve one’s ability to spell correctly. This talk explores choices in the design and use of AI tools to help with decision making and the importance of rigorous measurement and experimentation to maximize the benefits and minimize the risks.
Kahani: Visual storytelling through culturally nuanced images
Sameer Segal, Principal Research Software Development Engineer, Microsoft Research India
Image generation models can produce visually stunning images from natural language descriptions, but they often lack cultural awareness and nuances. These models may rely on stereotypes and fail to understand local words, which require heavy fixes like modifying or significantly fine tuning the model. Image generation can also require sophisticated prompting, beyond the abilities of many laypeople.
This talk looks at Kahani, a Microsoft Research project focused on developing a visual storytelling prototype that allows people to create visually striking and culturally nuanced images just by describing them in their local languages. Kahani leverages state-of-the-art techniques like inpainting and models like Segment Anything and GPT-4V(ision) to generate feedback for the candidate images.
Closing remarks and announcements
Ashley Llorens, VP and Distinguished Scientist, Microsoft
The acceleration of AI underscores the importance of engagement across disciplines, organizations, and geographies. This session introduced the first cohort of fellows for Microsoft Research’s AI & Society Fellows (opens in new tab) program, which aims to foster deep interdisciplinary collaboration that maximizes the value of AI for people and society. The session also provided an update on the Accelerate Foundation Models Research (opens in new tab) (AFMR) program, which issues grants that make leading models, hosted through Microsoft Azure, accessible to academic research teams. To date, AFMR grants are supporting nearly 200 projects across 80 research institutions around the world. These projects include work in AI model innovation and evaluation, responsible AI, health, AI for scientific discovery, and more.
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