Standing on the banks of the Seine, I found myself marveling at the beauty of “April in Paris” (cue the 1930s song). Perhaps it was the scent of the flowers in bloom in the Jardin du Luxembourg or the warmth of the Continental spring. But, most likely, my contentment stemmed from the success of the just-completed Microsoft Research Machine Learning Summit (opens in new tab), which took place April 22 to 24 in the “City of Light” on Le Campus de Microsoft France (opens in new tab).
The event brought together more than 230 attendees and presenters, including thought leaders from computer science, engineering, statistics, and mathematics. Through keynotes, demos, and panel discussions, we highlighted some of the key challenges in this new era of machine learning and explored the next generation of approaches, techniques, and tools that researchers and scientists need to exploit the information revolution for the benefit of society.
As exciting as the in-person event was, I was equally enthused by the reception of our streaming broadcast (opens in new tab) of key presentations and interviews, which was viewed by some 3,000 people around the globe. The live, online presentation not only made it possible for many more people to view the summit, it gave a broader group of students and researchers an opportunity to engage directly with some of the top experts in the field of machine learning, including Andrew Blake, director of Microsoft Research Cambridge, and Judea Pearl, professor emeritus at UCLA. I was pleased that many from the online audience posed questions about computer vision to Professor Blake, and difficult questions about probability and causality to Professor Pearl.
Microsoft Research Blog
Microsoft Research Forum Episode 3: Globally inclusive and equitable AI, new use cases for AI, and more
In the latest episode of Microsoft Research Forum, researchers explored the importance of globally inclusive and equitable AI, shared updates on AutoGen and MatterGen, presented novel use cases for AI, including industrial applications and the potential of multimodal models to improve assistive technologies.
There was hardly an area of machine learning that wasn’t explored in depth at the summit—from the aforementioned topics of computer vision and causality, to insightful presentations on Bayesian statistics and the use of machine learning techniques in the realm of social media and large-scale learning.
Of course the food was outstanding (it was Paris, after all), and meals were made all the more enjoyable by the stimulating conversation of our companions and the spectacular views of Paris from the thirty-fourth floor of our hotel. But for me, the most exciting moments were the intense discussions I observed taking place during breaks and the social events, and the sense that seeds of exciting new ideas were being planted that would germinate in the months and years ahead.
—Chris Bishop (opens in new tab), Distinguished Scientist, Microsoft Research Cambridge
Learn More
- Microsoft Research Machine Learning Summit On Demand (opens in new tab)
- Microsoft Research Machine Learning Summit (opens in new tab)
- Microsoft Research France (opens in new tab)
- Machine Learning at Microsoft Research (opens in new tab)
- Computer Science at Microsoft Research Connections (opens in new tab)