So here’s the deal: We’ve all been hearing about AI for a while now, but things have recently kicked up a notch. AI agents aren’t just some futuristic concept. They’re showing up everywhere—from your online shopping cart to hospital reception desks.
The “Last Mile Problem” illustrates how achieving near-perfect accuracy (99.9%) in quality inspection dramatically increases in difficulty, underscoring the value of AI-powered synthetic data.
In 2025, sustainability is no longer optional—it’s a strategic imperative. Manufacturers, responsible for nearly 40% of global material waste, face rising demands to reduce emissions, cut waste, improve product consistency, and enhance efficiency.
Artificial intelligence’s relentless march has sparked excitement and apprehension across the business landscape.
You can’t get big without thinking big right from the start. As an entrepreneur starting a business, it’s easy to see yourself as “the little guy.” If you do, you’ll forever stay the little guy.
Metamaterials are synthetic materials with microscopic structures that give the overall material exceptional properties.
In metamaterials design, the name of the game has long been “stronger is better.”
Beehive Industries leverages cutting-edge additive manufacturing to create precision components for jet engines in collaboration with Oak Ridge National Laboratory’s Manufacturing Demonstration Facility.
When Jonaaron Jones started his master’s degree at the University of Tennessee-Knoxville (UT), his mentor invited him to visit the Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory (ORNL).
Ryan Walton (left) and Ryan Lewis orient a WiSPR unit for testing.
A team from MIT Lincoln Laboratory has built and demonstrated wide-band selective propagation radar (WiSPR), a system capable of seeing out various distances at millimeter-wave (mmWave or MMW) frequencies.
What’s the hottest thing in electronics and high-performance computing? In a word, it’s “cool.”
One of the key findings in Greenlight Guru’s 2025 Medical Device Industry Re
Using a novel relevance framework developed at MIT, the robot identifies and prioritizes objects in the scene to autonomously assist humans in a seamless, intelligent, and safe manner.
For a robot, the real world is a lot to take in. Making sense of every data point in a scene can take a huge amount of computational effort and time. Using that information to then decide how to best help a human is an even thornier exercise.
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