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MIT


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 …

Modern machine-learning models, such as neural networks, are often referred to as “black boxes” because they are so complex that even the researchers who design them can’t fully understand how they make predictions. To provide some insights, researchers use explanation methods that seek to describe individual model decisions. For example, they may highlight words in …

Humans observe the world through a combination of different modalities, like vision, hearing, and our understanding of language. Machines, on the other hand, interpret the world through data that algorithms can process. So, when a machine “sees” a photo, it must encode that photo into data it can use to perform a task like image …

Soft, pneumatic actuators might not be a phrase that comes up in daily conversations, but more likely than not you might have benefited from their utility. The devices use compressed air to power motion, and with sensing capabilities, they’ve proven to be a critical backbone in a variety of applications such as assistive wearables, robotics, …

From “Star Wars” to “Happy Feet,” many beloved films contain scenes that were made possible by motion capture technology, which records movement of objects or people through video. Further, applications for this tracking, which involve complicated interactions between physics, geometry, and perception, extend beyond Hollywood to the military, sports training, medical fields, and computer vision …

  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 …

Labeling data can be a chore. It’s the main source of sustenance for computer-vision models; without it, they’d have a lot of difficulty identifying objects, people, and other important image characteristics. Yet producing just an hour of tagged and labeled data can take a whopping 800 hours of human time. Our high-fidelity understanding of the …

The notion of a large metallic robot that speaks in monotone and moves in lumbering, deliberate steps is somewhat hard to shake. But practitioners in the field of soft robotics have an entirely different image in mind — autonomous devices composed of compliant parts that are gentle to the touch, more closely resembling human fingers …

Students in the MIT course 6.036 (Introduction to Machine Learning) study the principles behind powerful models that help physicians diagnose disease or aid recruiters in screening job candidates.   Now, thanks to the Social and Ethical Responsibilities of Computing (SERC) framework, these students will also stop to ponder the implicationsof these artificial intelligence tools, which sometimes come …

IBM Research is working on new ways to generate material designs with AI with dozens of examples for the training model, instead of the tens of thousands often required. Over the last few years, we’ve seen that advances in deep-learning Learn about how using generative models to come up with new ideas, we can dramatically accelerate …