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…or a specific DNN [deep neural network],” Andrews explained. “We'll release a series of these over the coming months. By staying on the GPU, we're seeing up to a 3X speedup on Xavier and a 7X improvement on Orin on our type adaptation benchmark, which we tested running ROS 2 Foxy and Humble. Hardware acceleration is a hot topic in…
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…FIT funding to add artificial neural networks (ANNs) into their software. “Our software makes it simple and cost effective for companies to enter and scale additive manufacturin,” says Stephan Kühr, CEO, 3YOURMIND. “By adding more machine learning to our software we will multiply the effectiveness of AM programs. 3YOURMIND is developing the software infrastructure for a level of automation we…
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…2018, explaining how Google uses neural networks to speed up Gmail users’ email composition in a blog post, Yonghui Wu, Principal Engineer of the Google Brain Team, wrote, “Smart Compose is a new feature in Gmail that uses machine learning to interactively offer sentence completion suggestions as you type, allowing you to draft emails faster. Building upon technology developed for…
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…is capable of running multiple neural networks in parallel to process data and drive action. Each SparkFun JetBot AI Kit includes the following: NVIDIA Jetson Nano Developer Kit; Robot Platform Chassis and all Prototyping Electronics; 64GB MicroSD card—pre-flashed with the JetBot Image; 145 Field of View, wide-angle camera module; Wi-Fi adapter; serial controlled motor driver; and micro OLED Breakout. SparkFun…
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…is sure if AI and neural networks will allow some distribution centers to find brand-new ways of pre-staging goods to meet demands or if customers will adopt local lockers and pick-up locations en masse. The future is uncertain and exciting. What we do see as necessary for growing in that future is the ability for the supply chain, and every…
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…technologies such as AI for neural networks and computer vision, data streaming, storage and analytics from the edge to the cloud. But how do we make this technology “just work” for the people who are operating or working alongside the robots? One of the key behind-the-scenes components is what the Amazon Robotics team calls “comprehensive device management,” or CDM. It’s…
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…described the use of deep neural networks (DNNs) for “trainable feature extractors” in quality inspection. In other AI techniques, trying to train for all possible variations leads to infinite branching. “The system needs to correct wrong inferences,” Gorchet said. “We've replaced deduction with induction and added the ability to add knowledge on the fly,” he added. “Systems need less training…
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…“I was looking at using neural networks to model how people grasped objects and computer vision for manipulation back in 1994. I very rarely look back, and it was good work.” ACM also noted that Howard introduced fuzzy logic methods to model environmental uncertainty that advanced terrain classification in field robotics. NASA's SnoMote robots studied the effects of global warming…
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…that all NVIDIA inference deep neural networks (DNNs) will be available on NVIDIA GPU Cloud (NGC) as a ROS package with examples for image segmentation and pose estimation. In addition, the New Synthetic Data Generation (SDG) workflow will allow NVIDIA Isaac Sim users to create production-quality datasets at scale for vision AI training. The company claimed that Isaac Sim on…
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…landing-control algorithm that utilizes deep neural networks. With a better understanding of the environment, LEO could make its own decisions about the best combination of walking, flying, or hybrid motion based on what is safest and what uses the least amount of energy. “Right now, LEO uses propellers to balance during walking, which means it uses energy fairly inefficiently,” said…
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…perception models based on deep neural networks (DNNs). These packages can reduce the load on the host CPU while providing significant performance gain, said NVIDIA. “DNN models can be used as a plug-in to develop robots,” said Gopalakrishna. “Developers could take domain-specific data for, say, a hospital, a warehouse, or a store. They could deploy a diverse set of models…
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…In addition, AO’s ensemble deep-learning neural networks power sonar-data analysis. They empower predictions that are more accurate than those of individual models, claimed Terradepth. Platform users can display seafloor objects within respective interest regions. “Our ocean data-as-a-service model will leverage our browser-based, cloud infrastructure to make accessible valuable and mission-critical data in a secure manner to internal stakeholders, as well…
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…data for training DNNs [deep neural networks] for robotics use cases. NVIDIA launched new computing platforms specifically for robotics and edge AI use cases. Key announcements include an industrial version of the flagship Jetson AGX Xavier system-on-module (SOM) and the new next-generation Jetson AGX Orin platform built on the NVIDIA Ampere architecture. It brings unprecedented computing power—200 TOPS [trillions of…
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…that with deep learning or neural networks.” “For a collaborative robot, if the end customer can adjust it after it's delivered, its questionable if you'd need someone to come out every time you need to make a minor change,” he added. “Today, a lot of devices are sold in Europe that don't comply with current safety laws—that's a much bigger…
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…how Thermal Ranger uses convolutional neural networks (CNNs) to locate and identify the thermal signatures of pedestrians and animals in the dark with a single infrared camera. “The technology stack includes everything from pre-processing, sensor fusion, localization data, and decision making to the actuator system,” Gershman told Robotics 24/7. “We built the sensor and reference camera system and the perception…
Ultrasonic sensing enhances robotics perception
Cybernetix Ventures’ event kicks off Robotics Tech Week 2026 slate of events
Preview the manufacturing and warehouse components that will be on the…
Preview the manufacturing and warehouse robots and software that will be on…
