Driven by shifts in consumer behavior and the pandemic, e-commerce continues its explosive growth and transformation. As a result, logistics and transportation firms find themselves at the forefront of a parcel delivery revolution. This new reality is especially evident in last-mile delivery, which is now the most expensive element of supply chain logistics. It represents more than 41%
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Maritime startup Orca AI is pioneering safety at sea with its AI-powered navigation system, which provides real-time video processing to help crews make data-driven decisions in congested waters and low-visibility conditions. Every year, thousands of massive 100-million-pound vessels, ferrying $14T worth of goods, cross the world��s oceans and waterways, fighting to keep to tight deadlines.
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NVIDIA cuOpt is an accelerated optimization engine for solving complex routing problems. It efficiently solves problems with different aspects such as breaks, wait times, multiple cost and time matrices for vehicles, multiple objectives, order-vehicle matching, vehicle start and end locations, vehicle start and end times, and many more. More specifically, cuOpt solves multiple variants of��
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This week��s model release features NVIDIA cuOpt, a world-record-breaking accelerated optimization engine that helps teams solve complex routing problems and deliver new capabilities. It enables organizations to reimagine logistics, operations research, transportation, and supply chain optimization. NVIDIA cuOpt facilitates many logistics optimization use cases, including: Ultimately��
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The need for a high-fidelity multi-robot simulation environment is growing rapidly as more and more autonomous robots are being deployed in real-world scenarios. In this post, I will review what we used in the past at Cogniteam for simulating multiple robots, our current progress with NVIDIA Isaac Sim, and how Nimbus can speed up the development and maintenance of a multi-robot simulation with��
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Generative AI has marked an important milestone in the AI revolution journey. We are at a fundamental breaking point where enterprises are not only getting their feet wet but jumping into the deep end. With over 50 frameworks, pretrained models, and development tools, NVIDIA AI Enterprise, the software layer of the NVIDIA AI platform, is designed to accelerate enterprises to the leading edge��
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Mailroom workers pick up mail and parcels from different stations and deliver them to various recipients. They know that some envelopes are time-sensitive so they use their knowledge to plan routes with the shortest possible delivery time. This mail delivery puzzle can be mathematically addressed by using techniques from operations research, a discipline that deals with applying analytical��
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Dynamic programming (DP) is a well-known algorithmic technique and a mathematical optimization that has been used for several decades to solve groundbreaking problems in computer science. An example DP use case is route optimization with hundreds or thousands of constraints or weights using the Floyd-Warshall all-pair shortest paths algorithm. Another use case is the alignment of reads for��
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Utilities are challenged to integrate distributed clean energy resources��such as wind farms, rooftop solar, home batteries, and electric vehicles��onto legacy electric grid infrastructure. Existing systems were built to manage a one-way flow of power from a small number of industrial-scale generation plants, often run using coal, natural gas, or nuclear. Sign up for Edge AI News to stay up��
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Each day, energy flows throughout our lives �C from the fuel that powers cars and planes, to the gas used for stove top cooking, to the electricity that keeps the lights on in homes and businesses. Oil, gas, and electricity are mature commodity markets, but AI is transforming the processes used to produce, transport, and deliver these resources. Enter AI deployed at the edge: on oil rigs��
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