{"id":34001,"date":"2026-07-01T15:00:00","date_gmt":"2026-07-01T20:00:00","guid":{"rendered":"https:\/\/www.ecoticias.com\/en\/?p=34001"},"modified":"2026-07-01T06:29:10","modified_gmt":"2026-07-01T11:29:10","slug":"scientists-at-mit-have-created-a-robot-with-an-elephants-memory-that-promises-to-tell-you-where-you-left-your-keys-last-night-and-it-does-so-in-a-matter-of-seconds","status":"publish","type":"post","link":"https:\/\/www.ecoticias.com\/en\/scientists-at-mit-have-created-a-robot-with-an-elephants-memory-that-promises-to-tell-you-where-you-left-your-keys-last-night-and-it-does-so-in-a-matter-of-seconds\/34001\/","title":{"rendered":"Scientists at MIT have created a robot with an \u201celephant\u2019s memory\u201d that promises to tell you where you left your keys last night\u2014and it does so in a matter of seconds"},"content":{"rendered":"\n

Could a robot one day tell you where you left your keys, wallet, or an unfinished part on a factory floor<\/a>? Researchers at the Massachusetts Institute of Technology have developed a memory system<\/a> that moves a step in that direction, giving robots a way to remember what they saw, where they saw it, and when it happened.<\/p>\n\n\n\n

The system is called Describe Anything, Anywhere, Anytime, at Any Moment<\/a>, or DAAAM. It lets a moving robot build a detailed map of its surroundings and then answer plain-language questions about objects in that space, fast enough for real-time use<\/a>, according to MIT News<\/a>.<\/p>\n\n\n\n

A map that remembers<\/h2>\n\n\n\n

A regular robot map can show walls, doors, furniture, and paths. But that is not the same as remembering that the red bike with a flat tire was near a specific building, or that a tool was left in a bin yesterday evening.<\/p>\n\n\n\n

DAAAM is designed for that second kind of memory. The researchers call it “spatiotemporal memory,” which means a memory that connects place with time, much like people do when they retrace their steps after losing something.<\/p>\n\n\n\n

The team behind DAAAM<\/h2>\n\n\n\n

Luca Carlone<\/a>, an associate professor in MIT\u2019s Department of Aeronautics and Astronautics and director of the SPARK Laboratory, worked on the project with lead author Nicolas Gorlo<\/a>, an MIT graduate student, and Lukas Schmid<\/a>, a former MIT researcher who is now a professor at the University of Technology Nuremberg.<\/p>\n\n\n\n

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Read More: They hid the number zero from an artificial intelligence system in the hope that it would discover it on its own; what happened teaches us an important lesson about the future of AI<\/a><\/h3>\n<\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n

Carlone\u2019s central point is simple enough. If robots are going to work beside people, they need to understand requests in the way people actually speak, not just through rigid commands or labels.<\/p>\n\n\n\n

\"MIT
MIT\u2019s DAAAM system builds a detailed memory map of objects and places, helping robots answer questions about what they saw and where they saw it.<\/figcaption><\/figure>\n\n\n\n

Why robot maps fall short<\/h2>\n\n\n\n

Computer vision systems can often describe objects in impressive detail. Robotic mapping systems can also build three-dimensional layouts of rooms, buildings, or campuses.<\/p>\n\n\n\n

The trouble is that these strengths do not always meet in one fast system. A robot may know the shape of a room without knowing much about the objects inside it, or it may describe objects one by one so slowly that the method is not useful while the robot is moving.<\/p>\n\n\n\n

A faster way to store details<\/h2>\n\n\n\n

DAAAM tries to solve that problem by grouping nearby objects as the robot travels. It also chooses key frames, which are the clearest views of several objects at once, so the system can describe many things in parallel instead of wasting time on every single camera frame.<\/p>\n\n\n\n

That choice matters in the real world, where a robot may pass hundreds of objects in just a few minutes. The team reports that this approach can speed up the description process tenfold, and Gorlo summed up the idea with a short line, “We annotate every object only once.”<\/p>\n\n\n\n

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