Originally published on July 29, 2024, this post was updated on October 8, 2024. Robots need to be adaptable, readily learning new skills and adjusting to their surroundings. Yet traditional training methods can limit a robot’s ability to apply learned skills in new situations. This is often due to the gap between perception and action, as well as the challenges in transferring skills across…
]]>The application of robotics is rapidly expanding in diverse environments such as smart manufacturing facilities, commercial kitchens, hospitals, warehouse logistics, and agricultural fields. The industry is shifting towards intelligent automation, which requires enhanced robot capabilities to perform functions including perception, mapping, navigation, load handling, object grasping…
]]>NVIDIA is hosting a webinar with live Q&A at 10 am PDT on Oct. 14 as a part of the Emerging Chapters Educational Series. This technical session is open to anyone looking to learn beginner and intermediate level concepts and applications that show how to build efficient conversational AI pipelines.
]]>Businesses are constantly overhauling their existing infrastructure and processes to be more efficient, safe, and usable for employees, customers, and the community. With the ongoing pandemic, it’s even more important to have advanced analytics apps and services in place to mitigate risk. For public safety and health, authorities are recommending the use of face masks and coverings to…
]]>Whether to employ mixed precision to train your TensorFlow models is no longer a tough decision. NVIDIA’s Automatic Mixed Precision (AMP) feature for TensorFlow, recently announced at the 2019 GTC, features automatic mixed precision training by making all the required model and optimizer adjustments internally within TensorFlow with minimal programmer intervention.
]]>Neural networks with thousands of layers and millions of neurons demand high performance and faster training times. The complexity and size of neural networks continue to grow. Mixed-precision training using Tensor Cores on Volta and Turing architectures enable higher performance while maintaining network accuracy for heavily compute- and memory-intensive Deep Neural Networks (DNNs).
]]>The NVIDIA Transfer Learning Toolkit is now NVIDIA TAO Toolkit. Over the past several years, NVIDIA has been developing solutions to make AI and its benefits accessible to every industry. NVIDIA Transfer Learning Toolkit specifically allows developers looking into faster implementation of Intelligent Video Analytics (IVA) systems use deep learning and take their application from prototype to…
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