When designing new robots, engineers often look to nature for inspiration. They base their robots on the designs and behaviors of snakes, fish, humans, and more, such as sea slugs, whose feeding behaviors have been studied in recent research by the Carnegie Mellon University Biohybrid and Organic Robotics group under the direction of Vickie Webster-Wood, associate professor of mechanical engineering.
Today, we're adding a new, highly specialized tool to the Gemma 3 toolkit: Gemma 3 270M, a compact, 270-million parameter model.
Today, we're adding a new, highly specialized tool to the Gemma 3 toolkit: Gemma 3 270M, a compact, 270-million parameter model.
Today, we're adding a new, highly specialized tool to the Gemma 3 toolkit: Gemma 3 270M, a compact, 270-million parameter model.
A new AI-powered tool created by researchers at Carnegie Mellon University's School of Computer Science could change the way we manufacture and build things.
The manufacturing and logistics industries are undergoing a significant transformation due to the integration of AI, digital twins, and collaborative robots. AI acts as the intelligent core, optimizing cobot control, predictive maintenance, and supply chain management.
Scientists have developed a lightning-fast AI tool called HEAT-ML that can spot hidden “safe zones” inside a fusion reactor where parts are protected from blistering plasma heat. Finding these areas, known as magnetic shadows, is key to keeping reactors running safely and moving fusion energy closer to reality.
Science frequently draws inspiration from the natural world. After all, nature has had billions of years to perfect its systems and processes. Taking their cue from mollusk catch muscles, researchers have developed a low-voltage, muscle-like actuator that can help insect-scale soft robots to crawl, swim and jump autonomously in real-world settings. Their work solves a long-standing challenge in soft robotics: enabling tiny robots to move on their own without sacrificing power or precision.
AI agents are moving fast—from “experimental sidekicks” to full-fledged members of the enterprise workforce. They’re writing code, creating reports, handling transactions, and even making decisions without waiting for a human to click approve. That autonomy is what makes them useful—and […]
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Onsite mobile robotic microfactory builds homes faster, safer and with minimal waste. AI-enabled automation slashes build time by 70%, costs by 30% compared to conventional methods.
To effectively tackle a variety of real-world tasks, robots should be able to reliably grasp objects of different shapes, textures and sizes, without dropping them in undesired locations. Conventional approaches to enhancing the ability of robots to grasp objects work by tightening the grip of a robotic hand to prevent objects from slipping.
Scientists have designed swarms of microscopic robots that communicate and coordinate using sound waves, much like bees or birds. These self-organizing micromachines can adapt to their surroundings, reform if damaged, and potentially undertake complex tasks such as cleaning polluted areas, delivering targeted medical treatments, or exploring hazardous environments.
Modern robotic systems—in drones or autonomous vehicles, for example—use a variety of sensors, ranging from cameras and accelerometers to GPS modules. To date, their correct integration has required expert knowledge and time-consuming calibration.
Animals like bats, whales and insects have long used acoustic signals for communication and navigation. Now, an international team of scientists has taken a page from nature's playbook to model micro-sized robots that use sound waves to coordinate into large swarms that exhibit intelligent-like behavior.
Let us once discuss what these industry leaders teach us about tracking lean manufacturing software, why manual KPI tracking methods are losing relevance, and how your factory- from the smallest to a giant-would benefit from the power of digital solutions for manufacturing.