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.
]]>When working with embedded systems such as the Jetson modules, you must optimize your application based on your power budget and compute resources. To avoid performance or even thermal throttling issues, monitoring these resources becomes really important. Jetson modules are designed with a GPU, CPU, and various AI accelerators. They also feature a high-efficiency power management integrated…
]]>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…
]]>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…
]]>At GTC 2022, NVIDIA announced the Jetson Orin Nano series of system-on-modules (SOMs). They deliver up to 80X the AI performance of NVIDIA Jetson Nano and set the new standard for entry-level edge AI and robotics applications. For the first time, the Jetson family now includes NVIDIA Orin-based modules that span from the entry-level Jetson Orin Nano to the highest-performance Jetson AGX Orin.
]]>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…
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