Open ad-hoc categorization approach combines language guidance with visual clustering to learn contextualized features for flexible image interpretation.
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making
EPFL roboticists have shown that when a modular robot shares power, sensing, and communication resources among its individual units, it is significantly more resistant to failure than traditional robotic systems, where the breakdown of one element often means a loss of functionality.
MIT researchers' DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
Matroid builds no-code computer-vision detectors that can spot everything from microscopic material defects to real-time safety hazards on a factory floor.
In large-scale warehousing and distribution operations, conveyor belts are an essential infrastructure that must operate with near-zero downtime to ensure the timely delivery of products. The presence of loose or foreign items on a conveyor belt can pose a serious risk to these operations.
In this post, we'll walk through how to evaluate that progress using the same metrics our platform provides automatically, so you can build detectors that get smarter, sharper, and more reliable over time.
Open ad-hoc categorization approach combines language guidance with visual clustering to learn contextualized features for flexible image interpretation.
To bring AI into the real world, we often need a "bridge" to close the gap between those giant machines and the cameras and robot arms on the production line. At Matroid, we call these "AI Edge Compute Units".
Drs. Linda Katehi and Jian Tao are developing digital twin technology to create customizable, AI-powered sensor systems that can be built faster, more affordably and with better performance.
EPFL researchers are developing robotic beehive frames that help locate honey stores inside of beehives over time, without relying on cameras. The aim is to develop new observation tools to study honeybee behavior that better fit the bees' natural way to occupy space compared to current methods.
Did you miss ATCx AI for Engineers 2025? Catch up on key insights, real-world AI use cases, and how the event showcased AI's growing role in transforming engineering workflows, design, and smart manufacturing.
Traditional processors are inefficient in certain contexts, wasting energy on data movement rather than computation. As a result, the industry is shifting focus to maximizing performance per watt, highlighting the need to rethink compute architecture to meet real-world constraints.