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.
]]>Expanding the open-source Meta Llama collection of models, the Llama 3.2 collection includes vision language models (VLMs), small language models (SLMs), and an updated Llama Guard model with support for vision. When paired with the NVIDIA accelerated computing platform, Llama 3.2 offers developers, researchers, and enterprises valuable new capabilities and optimizations to realize their…
]]>Note: As of January 6, 2025, VILA is now part of the Cosmos Nemotron VLM family. NVIDIA is proud to announce the release of NVIDIA Cosmos Nemotron, a family of state-of-the-art vision language models (VLMs) designed to query and summarize images and videos from physical or virtual environments. Cosmos Nemotron builds upon NVIDIA’s groundbreaking visual understanding research including VILA…
]]>Recently, NVIDIA unveiled Jetson Generative AI Lab, which empowers developers to explore the limitless possibilities of generative AI in a real-world setting with NVIDIA Jetson edge devices. Unlike other embedded platforms, Jetson is capable of running large language models (LLMs), vision transformers, and stable diffusion locally. That includes the largest Llama-2-70B model on Jetson AGX Orin at…
]]>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…
]]>Today NVIDIA announced Jetson Xavier NX, the world’s smallest, most advanced embedded AI supercomputer for autonomous robotics and edge computing devices. Capable of deploying server-class performance in a compact 70x45mm form-factor, Jetson Xavier NX delivers up to 21 TOPS of compute under 15W of power, or up to 14 TOPS of compute under 10W. The Jetson Xavier NX module (Figure 1) is pin…
]]>NVIDIA announced the Jetson Nano Developer Kit at the 2019 NVIDIA GPU Technology Conference (GTC), a $99 computer available now for embedded designers, researchers, and DIY makers, delivering the power of modern AI in a compact, easy-to-use platform with full software programmability. Jetson Nano delivers 472 GFLOPS of compute performance with a quad-core 64-bit ARM CPU and a 128-core integrated…
]]>The world’s ultimate embedded solution for AI developers, Jetson AGX Xavier, is now shipping as standalone production modules from NVIDIA. A member of NVIDIA’s AGX Systems for autonomous machines, Jetson AGX Xavier is ideal for deploying advanced AI and computer vision to the edge, enabling robotic platforms in the field with workstation-level performance and the ability to operate fully…
]]>Today, NVIDIA released JetPack 3.1, the production Linux software release for Jetson TX1 and TX2. With upgrades to TensorRT 2.1 and cuDNN 6.0, JetPack 3.1 delivers up to a 2x increase in deep learning inference performance for real-time applications like vision-guided navigation and motion control, which benefit from accelerated batch size 1. The improved features allow Jetson to deploy greater…
]]>Today at an AI meetup in San Francisco, NVIDIA launched Jetson TX2 and the JetPack 3.0 AI SDK. Jetson is the world’s leading low-power embedded platform, enabling server-class AI compute performance for edge devices everywhere. Jetson TX2 features an integrated 256-core NVIDIA Pascal GPU, a hex-core ARMv8 64-bit CPU complex, and 8GB of LPDDR4 memory with a 128-bit interface.
]]>Deep Neural Networks (DNNs) are a powerful approach to implementing robust computer vision and artificial intelligence applications. NVIDIA Jetpack 2.3, released today, increases run-time performance of DNNs in embedded applications more than two-fold using NVIDIA TensorRT (formerly called GPU Inference Engine or GIE). With up to 20x higher power efficiency than an Intel i7 CPU during inference…
]]>Today, NVIDIA introduced Jetson TX1, a small form-factor Linux system-on-module, destined for demanding embedded applications in visual computing. Designed for developers and makers everywhere, the miniature Jetson TX1 (Figure 1) deploys teraflop-level supercomputing performance onboard platforms in the field. Backed by the Jetson TX1 Developer Kit, a premier developer community…
]]>NVIDIA’s Tegra K1 (TK1) is the first Arm system-on-chip (SoC) with integrated CUDA. With 192 Kepler GPU cores and four Arm Cortex-A15 cores delivering a total of 327 GFLOPS of compute performance, TK1 has the capacity to process lots of data with CUDA while typically drawing less than 6W of power (including the SoC and DRAM). This brings game-changing performance to low-SWaP (Size…
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