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
To reduce waste, the Refashion program helps users create outlines for adaptable clothing, such as pants that can be reconfigured into a dress. Each component of these pieces can be replaced, rearranged, or restyled.
Smart eyewear promises to transform how we see and interact with the world. Among its many potential advantages, the technology offers hands-free access to information, vision enhancement, and accessibility tools.
The no-code platform from Matroid trains ordinary cameras to act like expert inspectors, turning simple footage into a pixel-level defect checklist. Even a handheld GoPro can spot issues human eyes miss—using remarkably small datasets.
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.
The no-code platform from Matroid trains ordinary cameras to act like expert inspectors, turning simple footage into a pixel-level defect checklist. Even a handheld GoPro can spot issues human eyes miss—using remarkably small datasets.
In the world of automotive manufacturing, precision is not optional — it is mandatory. Every component, from wiring harnesses to interior panels to fasteners, must be installed correctly, in the correct sequence, at the correct tempo, every single time.
New machine learning framework bridges the embodiment gap between robots and humans and enables quadrupedal robots to perform versatile movements like pouring soda, organizing shoes, and even cleaning up cat litter.
Wearables have enjoyed a meteoric rise in popularity in recent years to the point that one in four of us now wear a smart connected device. Fifteen years ago, it was one in 100 people. This growth in ownership has been driven to an extent by convenience and integration.
In this article, we'll explore how three edge AI architectures; robotics, system-on-modules (SoMs), and medical devices, are driving this shift, and how MRAM and FeRAM are enabling smarter, more resilient memory at the edge.
AI has made incredible recent progress, but voice assistants are still plagued by the rigidity and lack of contextual awareness they launched with years ago. For most, voice remains an interface of last resort, reserved for occasionally pulling up directions or playing a song on a smart speaker.
High frequency radio waves can wirelessly carry the vast amount of data demanded by emerging technology like virtual reality, but as engineers push into the upper reaches of the radio spectrum, they are hitting walls. Literally.
While outdoor navigation using GPS technology is seamlessly integrated into everyday life, effective indoor navigation still presents a challenge. GPS signals are typically weaker or even non-existent inside large buildings, shopping malls, hospitals, airports, and industrial complexes.
In this episode, we explore how AI-powered eco-driving—smartly adjusting vehicle speeds to minimize stops and unnecessary acceleration—can reduce carbon emissions at city intersections by 11 to 22 percent.
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".