Found in Robotics News & Content, with a score of 57.96
March 14, 2022
ENOT.ai, which stands for “Embedded Neural Network Optimization Technology,” today released its optimization technology for developers of artificial intelligence and edge AI. The Riga, Latvia-based company said its framework can make deep neural networks faster, smaller, and more energy-efficient. “Today ... neural networks are widely used in production and applications,” stated Sergey Aliamkin, founder and CEO of ENOT. “Neural networks should be more effective in terms of consumption of computational resources and affordable.” Founded in 2021, ENOT said its team includes seven engineers, among whom are several Ph.D.s in computer science. They are also three-time winners of the global Low-Power…
Found in Robotics News & Content, with a score of 46.49
August 08, 2024
…in 2024, valuing the company at $2.6 billion. OpenAI neural network improvements in Figure 02 As part of the new humanoid, Figure 02 has a new addition for its artificial intelligence and neural network technology for, “speech-to-speech reasoning,” according to the company. When Figure AI announced its Series B round, including in the investors were OpenAI, Microsoft, NVIDIA and others. Along with the funding, OpenAI and Figure AI announced the companies had reached a collaboration agreement to develop AI models. The research combines OpenAI’s neural network and artificial intelligence with Figure’s humanoid hardware and software. Figure 02, according to the…
Found in Robotics News & Content, with a score of 37.02
April 10, 2021
…the most popular class of models is represented by neural networks, thanks to their ability to generalize. Neural networks can adapt to new, previously unseen data and recognize objects that they have never seen before. This capability is widely used in applications that require the recognition and handling of items that differ in shape, size, color, or material. Examples include automated picking of mixed objects from a bin, robotic unloading of pallets loaded with boxes of various shapes and sizes, and the singulation and sorting of all types of parcels. The benefit of classical neural networks is that they can…
Found in Robotics News & Content, with a score of 31.50
July 16, 2020
…deep learning workflow that uses NVIDIA GPUs to accelerate neural network training to scale up performance across nodes. “The NVIDIA Deep Learning Institute plays a crucial role in developing hands-on training and showcasing how to use new techniques like deep learning to solve complex problems,” says David Rich, director, MATLAB marketing, MathWorks. “This course offers a practical approach to deep learning that will help NVIDIA users to iterate quickly and converge on a solution that meets product and time-to-market requirements.” “There’s been a surge of interest in the Deep Learning with MATLAB course using NVIDIA GPUs,” said Will Ramey, senior…
Found in Robotics News & Content, with a score of 28.39
July 21, 2021
…through energy-efficient motion planning (EEMP). Novel motion-planning techniques like neural networks or machine learning (ML) offer to significantly streamline the creation of motion-control algorithms. These new algorithms could be essential in operating factory robots safely and efficiently. AI for robotics motion planning Creating an effective motion-planning algorithm can be extremely complex, and to date, no one has arrived at one single answer to the problem. The rise of human-robot interactions can create additional problems for motion planning algorithms. For the growing number of collaborative robots to be safe, they need to take paths that won’t pose a risk to nearby…
Found in Robotics White Papers & Archives, with a score of 27.47
September 25, 2024
…at their fingertips better than ever before. With robotics and automation generating mountains of valuable data for humans and neural networks to sift through, organizations can accurately monitor and track their inventory and workflows. When combined with generative AI analytics, robots can serve as mobile data platforms, informing decision-making and improving operational efficiency for commercial and industrial end users. In this Special Focus Issue Dexory delivers real-time visibility for warehouse operators Nokia AIMS automates inventory monitoring with AI-enabled drones ProGlove wearable scanners MARK the spot in the warehouse Brain Corp's Sense Suite helps address retail inventory challenges ...And more
Found in Robotics News & Content, with a score of 26.27
November 01, 2021
…CEO of Autobrains. “The representation problem is solved with neural networks, and the second is the annotation problem.” “My background was in electrical engineering and deep learning,” he told Robotics 24/7. “Another founder came out of the neurobiology lab. We realized that using a neural network as a classifier is not the right approach. Once you do that, you already limit something predefined by labels, even if you want to eventually classify and recognize.” Autobrains maps raw, unlabeled data onto high-dimensional and compressed signatures generated by a low-compute neural architecture. “Taking visual inputs and remembering the presentation of items in…
Found in Robotics News & Content, with a score of 26.18
August 11, 2022
…tackling this is through convenience stores — a huge network that supports daily life, especially in Japan, but is facing a labor shortage.” The company, founded in 2017, next plans to expand to convenience stores in the U.S., which it said is also plagued with a labor shortage in the retail industry — and where more than half of consumers say they visit one of the country’s 150,000 convenience stores at least once a month. Telexistence robots stock up at FamilyMart Telexistence will begin deploying its restocking robots, called TX SCARA, to 300 FamilyMart stores in August — and aims…
Found in Robotics News & Content, with a score of 25.48
May 25, 2023
…Modes” (Read paper, watch video) “nerf2nerf: Pairwise Registration of Neural Radiance Fields” (Read paper, watch video) “DexGrasp-1M: Dexterous Multi-Finger Grasp Generation Through Differentiable Simulation” (Read paper, watch video) Large language models among paper topics In addition, NVIDIA will present research on machine learning: “ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models” (Read paper, watch video) “DefGraspNets: Grasp Planning on 3D Fields With Graph Neural Nets” (Read paper, watch video) “CuRobo: Parellelized Collision-Free Robot Motion Generation” (Read paper, watch video) “RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control” (Read paper, watch video) “FewSOL: A Dataset for Few-Shot Object…
Found in Robotics News & Content, with a score of 25.38
May 15, 2020
…AI capabilities for deep learning. Engineers can now train neural networks in the updated Deep Network Designer app, manage multiple deep learning experiments in a new Experiment Manager app, and choose from more network options to generate deep learning code. R2020a introduces new capabilities specifically for automotive and wireless engineers in addition to hundreds of new and updated features for all users of MATLAB and Simulink. AI and Deep Learning “MathWorks provides a comprehensive platform for building AI-driven systems,” says David Rich, MATLAB marketing director. “We’ve taken three decades of product, consulting and support experiences and applied it to an…
Found in Robotics News & Content, with a score of 24.82
March 01, 2019
…various ways. The algorithms use mathematical models in a neural network to identify patterns in data and respond to them. This can be applied for pattern recognition in images, videos, sounds, text and any other type of data. In design, integrating deep learning and design processes can help bring better products to market more quickly. “Deep learning and design engineering can learn a lot from each other and generate surprising outcomes.” — Leslie Nooteboom, Humanising Autonomy Design tools can be applied to deep learning processes to help gather and annotate data, and develop real-world applications, according to Leslie Nooteboom, CDO…
Found in Robotics News & Content, with a score of 24.79
July 23, 2019
…This is 3YOURMIND’s vision for Agile Manufacturing. More specifically, 3YOURMIND will use the Pro 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 call agile manufacturing; the ability to quickly and accurately adapt production to customer needs and company resources.“ Sources: Press materials received from the company and additional…
