AI is consuming staggering amounts of energy—already over 10% of U.S. electricity—and the demand is only accelerating. Now, researchers have unveiled a radically more efficient approach that could slash AI energy use by up to 100× while actually improving accuracy. By combining neural networks with human-like symbolic reasoning, their system helps robots think more logically instead of relying on brute-force trial and error.
A guy spent $22,000 on a steel mold. Parts came back warped. The wall thickness was wrong. The factory said it was his design. He said it was their fault. Six months later, still no product. That story is not rare. It happens constantly to founders and engineers who skip the basics of injection molding. […]
Vecna Robotics, a provider of flexible material handling automation, has announced CaseFlow Voice, which the company says is the only case picking automation solution with fully integrated voice technology. CaseFlow Voice embeds Lucas Systems’ “Jennifer” voice capabilities directly into case picking workflows, enabling hands-free operations that improve worker productivity and accuracy while helping warehouses achieve […]
Scientists in Japan say they have developed a new approach – dubbed ‘HEAPGrasp’ – that improves robots’ grasping success rate for transparent and shiny objects, beyond reducing handling time, using only RGB camera The fields of manufacturing, logistics, and even restaurants are increasingly moving toward automation, with robots being employed for a wide range of […]
By Michael Santora, CEO at Logic Robotics Cities across the globe are wrestling with a stubborn challenge: congestion. While traffic often comes to mind first, logistics experts point out that the real bottleneck in many urban environments lies at the curb. Trucks not only clog intersections as they navigate narrow streets, but also occupy scarce […]
Robotics teams rarely struggle because a part cannot be printed at all. More often, they lose time because a part arrives with the wrong material, the wrong orientation, a missed drawing note, or small inconsistencies that only become obvious during assembly or testing. That is why speed alone is not enough. For robotics teams, a […]
Robots make work faster, cleaner, and more consistent. They also change how risk shows up on the floor. The danger is not only the moving arm, but also the in-between moments, when a cell is paused, a jam is cleared, or a quick adjustment turns into hands inside the fence. Operators sit closest to these […]
A new study put ChatGPT to the test by asking it to judge whether hundreds of scientific hypotheses were true or false—and the results were far from reassuring. While the AI got it right about 80% of the time on the surface, its performance dropped significantly when accounting for random guessing, revealing only modest reasoning ability. Even more concerning, it frequently contradicted itself when asked the exact same question multiple times, sometimes flipping answers back and forth.
Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The breakthrough could lead to powerful, low-energy supercomputers while revealing new secrets about how our brains process information.
A generative AI system can now analyze blood cells with greater accuracy and confidence than human experts, detecting subtle signs of diseases like leukemia. It not only spots rare abnormalities but also recognizes its own uncertainty, making it a powerful support tool for clinicians.
A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how systems evolve over time and reduces thousands of variables into compact equations that still capture real behavior. The method works across physics, engineering, climate science, and biology. Researchers say it could help scientists understand systems where traditional equations are missing or too complicated to write down.