Below are summaries of the Minsky Fellows' research:
Ben Bloomberg, Opera of the Future group
Ben’s research is concerned primarily with the orchestration of interactions between humans and machines to create new live experiences and artistic works. While much of the work in AI is concerned with learning and statistical pattern recognition, he believes that we must look beyond these methods to find the best approaches for humans and machines to come together in emotionally meaningful ways.
Marvin Minsky’s analysis of music and emotion is the basis for Ben’s work. His initial efforts have revolved around intelligent musical instruments and performance systems which use sensors to interpret the expression of performers emotionally. Ben’s Hyperproduction system uses a network of agents to process external stimuli modeled loosely on those in Minsky’s book, The Society of Mind. Ben hopes to expand the input and output capability to allow it to connect to more types of infrastructure—from lights to vehicles to HVAC systems—and he plans to expand possible processes to include new, advanced deep learning techniques. This will enable musical, emotional articulation of everyday objects and environments.
Bjarke Felbo, Scalable Cooperation group
Bjarke’s research concentrates on teaching machines to understand human emotion, at both individual and societal levels. This was Marvin Minsky's ultimate goal, as articulated in his 2006 book, The Emotion Machine. During Bjarke’s first year at the Media Lab, he has demonstrated his strong technical competencies by beating state-of-the-art deep learning algorithms across several benchmark datasets related to emotion modeling.
Going beyond the common computer science limitation of only beating benchmarks, Bjarke is also building fruitful collaborations with other research fields, including faculty from the MIT Department of Brain and Cognitive Sciences, in which he examines how machine learning can potentially help our understanding of human emotions. Another collaboration is with social and political scientists, where Bjarke identifies underlying factors affecting our society's opinions on climate change and race issues. He does this by applying his emotional machine learning techniques to analyze millions of posts from social media.
Kfir Schreiber, Molecular Machines group
The focus of Kfir’s research is in applied machine learning and AI for drug development. His premise is to develop novel AI and machine learning approaches alongside existing ideas, to transform the pharmaceuticals industry by reducing the complexity of new drug development in terms of both time and resources. Today, the time-to-market for a new drug is 15 years on average, while its research and development cost is over 2 billion dollars. Kfir hopes to harness the power of AI to reduce the time-to-market and cost significantly, allowing the development of drugs that are out of reach today. Currently, his work centers on the early pre-clinical phases. Current projects include protein folding, protein-protein interactions, and small molecule drug design.
In addition to his core research, Kfir is deeply interested in fundamental AI questions that were heavily inspired by Minsky's books and ideas. Some recent works include interaction between learning agents as seen in adversarial learning scenarios, intention inference in conflicts between mental agents, and ethics in AI.