The generative AI landscape is rapidly evolving, with new large language models (LLMs), visual language models (VLMs), and vision language action (VLA) models emerging daily. To stay at the forefront of this transformative era, developers need a platform powerful enough to seamlessly deploy the latest models from the cloud to the edge with optimized inferencing and open ML frameworks using CUDA.
]]>NVIDIA JetPack SDK powers NVIDIA Jetson modules, offering a comprehensive solution for building end-to-end accelerated AI applications. JetPack 6 expands the Jetson platform’s flexibility and scalability with microservices and a host of new features. It’s the most downloaded version of JetPack in 2024. With the JetPack 6.0 production release now generally available…
]]>Real-time AI at the edge is crucial for medical, industrial, and scientific computing because these mission-critical applications require immediate data processing, low latency, and high reliability to ensure timely and accurate decision-making. The challenges involve not only high-bandwidth sensor processing and AI computation on the hardware platform but also the need for enterprise-level AI…
]]>NVIDIA SDKs have been instrumental in accelerating AI applications across a spectrum of use cases spanning smart cities, medical, and robotics. However, achieving a production-grade AI solution that can deployed at the edge to support human and machine collaboration safely and securely needs both high-quality hardware and software tailored for enterprise needs. NVIDIA is again accelerating…
]]>Embedded edge AI is transforming industrial environments by introducing intelligence and real-time processing to even the most challenging settings. Edge AI is increasingly being used in agriculture, construction, energy, aerospace, satellites, the public sector, and more. With the NVIDIA Jetson edge AI and robotics platform, you can deploy AI and compute for sensor fusion in these complex…
]]>Robots are increasing in complexity, with a higher degree of autonomy, a greater number and diversity of sensors, and more sensor fusion-based algorithms. Hardware acceleration is essential to run these increasingly complex workloads, enabling robotics applications that can run larger workloads with more speed and power efficiency. The mission of NVIDIA Isaac ROS has always been to empower…
]]>The NVIDIA Jetson Orin Nano Developer Kit sets a new standard for creating entry-level AI-powered robots, smart drones, and intelligent vision systems, as NVIDIA announced at NVIDIA GTC 2023. It also simplifies getting started with the NVIDIA Jetson Orin Nano series. Compact design, numerous connectors, and up to 40 TOPS of AI performance make this developer kit ideal for transforming your…
]]>NVIDIA JetPack provides a full development environment for hardware-accelerated AI-at-the-edge on Jetson platforms. Previously, a standalone version of NVIDIA JetPack supports a single release of CUDA, and you did not have the ability to upgrade CUDA on a given NVIDIA JetPack version. NVIDIA JetPack is released on a rolling cadence with a single version of CUDA…
]]>With the Jetson Orin Nano announcement this week at GTC, the entire Jetson Orin module lineup is now revealed. With up to 40 TOPS of AI performance, Orin Nano modules set the new standard for entry-level AI, just as Jetson AGX Orin is already redefining robotics and other autonomous edge use cases with 275 TOPS of server class compute. All Jetson Orin modules and the Jetson AGX Orin Developer…
]]>The pace for development and deployment of AI-powered robots and other autonomous machines continues to grow rapidly. The next generation of applications require large increases in AI compute performance to handle multimodal AI applications running concurrently in real time. Human-robot interactions are increasing in retail spaces, food delivery, hospitals, warehouses, factory floors…
]]>Join the NVIDIA Triton and NVIDIA TensorRT community to stay current on the latest product updates, bug fixes, content, best practices, and more. AI machine learning (ML) and deep learning (DL) are becoming effective tools for solving diverse computing problems in various fields including robotics, retail, healthcare, industrial, and so on. The need for low latency, real-time responsiveness…
]]>Today, NVIDIA announced the Jetson Nano 2GB Developer Kit, the ideal hands-on platform for teaching, learning, and developing AI and robotics applications. The NVIDIA Jetson platform introduced six years ago revolutionized embedded computing by delivering the power of artificial intelligence to edge computing devices. NVIDIA Jetson today is widely used in diverse fields such as robotics, retail…
]]>Microsoft and NVIDIA have collaborated to build, validate and publish the ONNX Runtime Python package and Docker container for the NVIDIA Jetson platform, now available on the Jetson Zoo. Today’s release of ONNX Runtime for Jetson extends the performance and portability benefits of ONNX Runtime to Jetson edge AI systems, allowing models from many different frameworks…
]]>Today, NVIDIA announced the NVIDIA Jetson Xavier NX Developer Kit , which is based on the Jetson Xavier NX module. Delivering up to 21 TOPS of compute in a compact form factor with under 15W of power, Jetson Xavier NX brings server-level performance and cloud-native workflows to edge AI devices and autonomous machines. With the Jetson Xavier NX Developer Kit, you can create amazing AI…
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