Phantom AI, which develops advanced driver-assistance systems, is putting its technology on Renesas’ system on chip to provide computer vision, sensor fusion, and control capabilities.

The Qualcomm Robotics RB5 Platform helps developers tap into 5G and AI to create high-compute, power-efficient robots for a variety of industries.

Intel shared four research papers on new edge processing techniques, including one on a raycast accelerator that could improve visual SLAM accuracy while maintaining energy efficiency.

Columbia researchers have developeed a new optical phased array on chip at both near-infrared and blue wavelengths. It could advance autonomous navigation, augmented and virtual reality, and neuroscience.

Solid-state lidar such as the cameras from Sense Photonics could help increase warehouse safety by perceiving forklift forks more accurately.

‘Ferrobots,’ or magnetically controlled robots on a chip, promise to revolutionize medical diagnostic testing and other industries, just as Amazon’s warehouse robots have, said UCLA researchers.

Machine learning on edge devices could transform the manufacturing, healthcare, and energy industries. An AI executive explains why and the hardware involved.

Arbe, an Israel-based startup developing 4D radar technology that it claimed generates images 100 times more accurate than anything currently available on the market, raised funds for productization.

NVIDIA has partnered with Hackster to host the AI-at-the-Edge Challenge. The contest invites makers, robotics developers, and embedded technology enthusiasts to use the NVIDIA Jetson Nano Developer Kit to create an AI solution for a chance to win from $100K in prizes. Deadline to submit an entry using the NVIDIA Jetson Nano Developer Kit is…

Intel unveiled its 8 million-neuron neuromorphic system codenamed Pohoiki Beach today at the Defense Advanced Research Projects Agency (DARPA) Electronics Resurgence Initiative in Detroit. Consisting of 64 Loihi research chips, Intel claims Pohoiki Beach can be up to 1,000 times faster and 10,000 times more efficient than CPUs for autonomous driving, robotics and other applications.…

MIT researchers have developed a novel “photonic” chip that uses light instead of electricity — and consumes relatively little power in the process. The chip could be used to process massive neural networks millions of times more efficiently than today’s classical computers do. Neural networks are machine-learning models that are widely used for such tasks…

  NVIDIA’s Jetson Nano and Jetson Nano Development Kit. Low cost, yet very powerful, AI optimized compute resources such as NVIDIA’s Jetson Nano brings machine learning to the masses, and also has the potential of replacing the dominant paradigm of centralized, machine learning training and inferencing architectures. Synopsis During his keynote session at the recent…

NVIDIA’s Isaac SDK and Isaac Simulator, which were announced last month, are now available for robotics developers to download. The Isaac SDK toolbox offers developers access to Isaac applications, GEMs (robot capabilities), a Robot Engine, and the Isaac Sim. NVIDIA’s goal with its Isaac portfolio is to make it easier for manufacturers, researchers, and startups…

CLEVELAND and BOSTON — At the Robotics Summit & Expo 2019, experts from leading companies will discuss how the next generation of commercial robots will benefit from enabling technologies such as IoT, 5G, and cloud infrastructure. Keynote presenters from Amazon AWS, Microsoft, NVIDIA, and Qualcomm will also focus on the vital roles of AI and…

SAN JOSE, Calif. — Robotics developers are off to the races creating autonomous machines of the future, said NVIDIA Corp. this week. The company said it’s fueling their efforts with the NVIDIA Isaac software development kit, which will be publicly available soon as a free robotics developer toolbox for accelerating innovation and deployment. NVIDIA founder…

There was no shortage of robotics-related announcements today at NVIDIA’s GPU Tech Conference (GTC) in San Jose, California. We will start with NVIDIA’s Jetson AI computer platform adding support for AWS Robomaker, the cloud robotics service from Amazon Web Services. AWS RoboMaker makes it easier to develop, test and deploy intelligent robotics applications at scale.…

The Robot Report named NVIDIA a must-watch robotics company in 2019 due to its new Jetson AGX Xavier Module that it hopes will become the go-to brain for next-generation robots. Now there’s even more reason to keep an eye on NVIDIA’s robotics moves: the Santa Clara, Calif.-based chipmaker just opened its first full-blown robotics research…

NVIDIA announced at its Jetson Developer Meetup the Jetson AGX Xavier Module for autonomous machines, delivering up to 32 TeraOPs (TOPS) of accelerated computing capability. The NVIDIA Jetson AGX Xavier Module, which the company calls an AI computer, is now available for $1,099 (based on 1,000 unit volume). NVIDIA introduced the Jetson AGX Xavier developer…

MathWorks today announced the availability of its new GPU-accelerated container from the NVIDIA GPU Cloud (NGC) container registry for DGX Systems and other supported NGC platforms. Researchers and developers can now use the deep learning workflow in MATLAB and leverage multiple GPUs in NVIDIA DGX Systems, or on supported cloud service providers, and select NVIDIA…

NVIDIA introduced new developer platforms to power the next generation robotics and autonomous vehicles. NVIDIA founder and CEO Jensen Huang unveiled the Jetson AGX Xavier (robotics) and DRIVE AGX Xavier (self-driving cars) at the company’s GTC Japan event. The Jetson AGX Xavier includes a small computer module capable of up to 32 TOPs (trillion operations per second) and…