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MIT-IBM Watson AI Lab


MIT researchers have developed a technique for enabling artificial intelligence agents to think much farther into the future, which can improve the long-term performance of cooperative or competitive AI agents. Photo credit: Jose-Luis Olivares, MIT, with MidJourney Picture two teams squaring off on a football field. The players can cooperate to achieve an objective, and …

It’s a dilemma as old as time. Friday night has rolled around, and you’re trying to pick a restaurant for dinner. (Assuming there’s still reservations since you waited until the last minute to book). Anyways, should you go to your most beloved watering hole, or try a new establishment, in the hopes of discovering something …

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures. To do this, researchers train machine-learning models using vast datasets of video clips that show humans performing actions. However, not only is …

Imagine the booming chords from a pipe organ echoing through the cavernous sanctuary of a massive, stone cathedral. The sound a cathedral-goer will hear is affected by many factors, including the location of the organ, where the listener is standing, whether any columns, pews, or other obstacles stand between them, what the walls are made …

Imagine the booming chords from a pipe organ echoing through the cavernous sanctuary of a massive, stone cathedral.   The sound a cathedral-goer will hear is affected by many factors, including the location of the organ, where the listener is standing, whether any columns, pews, or other obstacles stand between them, what the walls are …

Malicious agents can use machine learning to launch powerful attacks that steal information in ways that are tough to prevent and often even more difficult to study. Attackers can capture data that “leaks” between software programs running on the same computer. They then use machine-learning algorithms to decode those signals, which enables them to obtain …

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 …

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 …

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 …

In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct. For instance, a machine-learning model might correctly predict that a skin lesion is cancerous, but it could have done so using an unrelated blip on a clinical photo. While tools exist to help experts make …