Artificial intelligence (AI) is the darling of businesses and governments because it not only promises to add tens of trillions to the gross domestic product (GDP), but it comes with all the excitement of action-packed movies or dopamine-drenched gaming. We are mesmerized by computer vision, natural language processing, and the uncanny predictions of recommendation engines….
The voracious appetite for energy from the world’s computers and communications technology presents a clear threat for the globe’s warming climate. That was the blunt assessment from presenters in the intensive two-day Climate Implications of Computing and Communications workshop held on March 3 and 4, hosted by MIT’s Climate and Sustainability Consortium (MCSC), MIT-IBM Watson…
Neurodegenerative diseases are defined by an increasingly widespread and debilitating death of nervous system cells, but they also share other grim characteristics: Their cause is rarely discernible and they have all eluded cures. To spur fresh, promising approaches and to encourage new experts and expertise to join the field, MIT’s Aging Brain Initiative (ABI) this…
MIT research scientists Pablo Rodriguez-Fernandez and Nathan Howard have just completed one of the most demanding calculations in fusion science — predicting the temperature and density profiles of a magnetically confined plasma via first-principles simulation of plasma turbulence. Solving this problem by brute force is beyond the capabilities of even the most advanced supercomputers. Instead,…
Pharmaceutical companies are using artificial intelligence to streamline the process of discovering new medicines. Machine-learning models can propose new molecules that have specific properties which could fight certain diseases, doing in minutes what might take humans months to achieve manually. But there’s a major hurdle that holds these systems back: The models often suggest new…
Not all data are created equal. But how much information is any piece of data likely to contain? This question is central to medical testing, designing scientific experiments, and even to everyday human learning and thinking. MIT researchers have developed a new way to solve this problem, opening up new applications in medicine, scientific discovery,…
Posted by Cat Armato and Callan Hajosy, Program Managers The 10th International Conference on Learning Representations (ICLR 2022) kicks off this week, bringing together researchers, entrepreneurs, engineers and students alike to discuss and explore the rapidly advancing field of deep learning. Entirely virtual this year, ICLR 2022 offers conference and workshop tracks that present some…
Figure 1: Summary of our recommendations for when a practitioner should BC and various imitation learning style methods, and when they should use offline RL approaches. Offline reinforcement learning allows learning policies from previously collected data, which has profound implications for applying RL in domains where running trial-and-error learning is impractical or dangerous, such as…
With e-commerce orders pouring in, a warehouse robot picks mugs off a shelf and places them into boxes for shipping. Everything is humming along, until the warehouse processes a change and the robot must now grasp taller, narrower mugs that are stored upside down. Reprogramming that robot involves hand-labeling thousands of images that show it…
Posted by Ting Chen and David Fleet, Research Scientists, Google Research, Brain Team Object detection is a long-standing computer vision task that attempts to recognize and localize all objects of interest in an image. The complexity arises when trying to identify or localize all object instances while also avoiding duplication. Existing approaches, like Faster R-CNN…