# U.S. Armed Forces Published articles for U.S. Armed Forces. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Clearing up a robot's fuzzy memory DevFeed: [Clearing up a robot's fuzzy memory]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-11-05T05:00:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Robot Manipulation](), [Image]() Tags: [aeronautical-and-astronautical-engineering](), [algorithms](), [artificial-intelligence](), [computer-science-and-technology](), [computer-vision](), [electrical-engineering-and-computer-science-eecs](), [environment](), [harry-zhang](), [laboratory-for-information-and-decision-systems-lids](), [luca-carlone](), [machine-learning](), [memory](), [mit-schwarzman-college-of-computing](), [nicolas-gorlo](), [object](), [research](), [robot](), [robotics](), [school-of-engineering](), [spatio-temporal-memory](), [system](), [u-s-armed-forces](), [uncertainty-quantification](), [vision-language-models]() ### AI overview UQ-DAAAM helps a robot detect and correct unreliable object descriptions in its map-based memory. It combines the vision-language model's confidence in a caption with its consistency against descriptions from other viewpoints. When uncertainty crosses a threshold, a heuristic selects useful additional views without rerunning the vision-language model; a language model then combines captions, favoring newer and less ambiguous ones. The researchers report that this resolves ambiguities for about 92% of objects using two additional captions per object, raises description accuracy by 5% over the state of the art, and improves answers about objects, locations, and when they were seen compared with baseline methods. The excerpt describes planned extensions to other robots and uncertainty-guided revisits; it does not report those as completed. ### Source excerpt A new system identifies and corrects unreliable object descriptions stored in a robot's memory, improving the robot's ability to interact with its environment. ## Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award DevFeed: [Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award]() Original publisher: [Read original article]() Author: Erin Lee | Lincoln Laboratory Published: 2026-09-11T13:45:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [software-development](), [Software]() Tags: [2026](), [ai](), [ai-assisted-catheterization-device](), [ai-guide](), [artificial-intelligence](), [asha-rajagopal](), [autonomus-medical-technologies](), [awards-honors-and-fellowships](), [devices](), [emergency-medicine](), [engineering](), [excellence-in-technology-transfer-awards](), [federal-laboratory-consortium-for-technology-transfer](), [field](), [funding](), [health-sciences-and-technology](), [industry](), [invention](), [lincoln-laboratory](), [mass-general-hospital](), [medical-device-invention](), [medical-devices](), [medicine](), [mgh](), [military-medics](), [mit-intellectual-property](), [mit-lincoln-laboratory](), [mit-startups](), [mit-technology-licensing-office-tlo](), [national-institutes-of-health-nih](), [nih-funding](), [portable](), [prototype](), [real-world](), [research](), [samuel-kesner](), [startup](), [startups](), [technology](), [u-s-armed-forces](), [u-s-army]() ### AI overview AI-GUIDE, a portable catheterization device developed by MIT Lincoln Laboratory and Massachusetts General Hospital, received the Federal Laboratory Consortium's 2026 Excellence in Technology Transfer Award. The project is transferring its prototype to AutonomUS Medical Technologies for commercialization. ### Source excerpt The handheld catheterization device AI-GUIDE, created by Lincoln Laboratory and Massachusetts General Hospital, promises improved health outcomes for injured service members and civilians. ## How novice coders can develop AI programs for military applications DevFeed: [How novice coders can develop AI programs for military applications]() Original publisher: [Read original article]() Author: Haley Wahl | MIT Lincoln Laboratory Published: 2026-07-07T17:25:00Z Content type: article Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Vibe coding](), [AI Development](), [AI Chat](), [Language models](), [Software Engineering](), [software-development]() Tags: [ai](), [ai-and-military](), [ai-assisted-target-recognition](), [ai-chatbots](), [ai-programming](), [ai-writing-software](), [artificial-intelligence](), [autonomous-striking](), [battlefield-communications](), [chatbots](), [chatgpt](), [claude](), [coding](), [computer-science-and-technology](), [daf-mit-ai-accelerator-phantom-program](), [gemini-llm](), [google-ai-studio-app](), [language-models](), [laura-niss](), [lincoln-laboratory](), [military-ai](), [mit-lincoln-laboratory](), [novice-coders](), [programming](), [remote-operating-modular-augmentation-device-romad-ai](), [research](), [security-and-military-studies](), [software](), [software-development](), [u-s-armed-forces](), [vibe-coding](), [vision-language-models-vlms]() ### AI overview A U.S. Air Force cadet with no coding experience used generative AI chatbots and a process called vibe-coding to develop a military application. The project examined whether nontechnical service members could create useful software for military problems. ### Source excerpt A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.