Built on eSmart Systems’ patent-pending Adaptive AI, the new platform lets utilities and technology companies build, deploy, ...
Tech Xplore on MSN
Improving AI models' ability to explain their predictions
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...
Microsoft's Phi-4-reasoning-vision-15B uses careful data curation and selective reasoning to compete with models trained on ...
Vietnam Investment Review on MSN
DFRobot showcases HUSKYLENS 2 AI vision module at embedded world
SHANGHAI, March 11, 2026 /PRNewswire/ -- From March 10 to 12, DFRobot is exhibiting at the RISC-V International booth (Hall 5, Booth 5-119) at embedded world 2026, presenting its latest HUSKYLENS 2 AI ...
As an ophthalmologist and technology commentator, I have been intrigued by how artificial intelligence and computer vision are transforming drone capabilities and reshaping modern warfare. In the new ...
Microsoft’s Phi-4-reasoning-vision-15B model shows how compact AI systems can combine vision and reasoning, signalling a broader industry move towards efficiency rather than simply building ever ...
In the new study, Apple taught an AI model to recognize hand gestures that weren’t part of its original training dataset.
People and computers perceive the world differently, which can lead AI to make mistakes no human would. Researchers are working on how to bring human and AI vision into alignment.
Computer scientists and weather scientists have taken the first steps toward creating an AI agent capable of analyzing and ...
At embedded world, on the DigiKey booth, Lucy Barnard speaks with Marta Barbero at Arduino, about the new Arduino product announcement.
Barbara is a tech writer specializing in AI and emerging technologies. With a background as a systems librarian in software development, she brings a unique perspective to her reporting. Having lived ...
Rest of World on MSN
Western AI models fail spectacularly in farms and forests abroad
Big tech’s AI tools trained on Western data often can’t recognize local crops, forests, or farming conditions without adaptation to local environments.
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