This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. 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 […]
Deploying Accelerated Llama 3.2 from the Edge to the Cloud Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Vision-language models (VLMs) combine the powerful language understanding of foundational LLMs with the vision capabilities of vision transformers (ViTs) by projecting text and images into the same embedding space. They can take unstructured multimodal data, reason over
Using Generative AI to Enable Robots to Reason and Act with ReMEmbR Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. NVIDIA AI Workbench is a free, user-friendly development environment manager that streamlines data science, ML, and AI projects on your system of choice: PC, workstation, datacenter, or cloud. You can develop, test, and prototype projects locally on
NVIDIA AI Workbench Simplifies Using GPUs on Windows Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This post is the third in a series on building multi-camera tracking vision AI applications. We introduce the overall end-to-end workflow and fine-tuning process to enhance system accuracy in the first part and second part. NVIDIA Metropolis
Simplifying Camera Calibration to Enhance AI-powered Multi-Camera Tracking Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. NVIDIA has announced the latest v0.15 release of NVIDIA TensorRT Model Optimizer, a state-of-the-art quantization toolkit of model optimization techniques including quantization, sparsity, and pruning. These techniques reduce model complexity and enable downstream inference frameworks like NVIDIA
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. New research aims to revolutionize video accessibility for blind or low-vision (BLV) viewers with an AI-powered system that gives users the ability to explore content interactively. The innovative system, detailed in a recent paper, addresses significant gaps
Interactive AI Tool Delivers Immersive Video Content to Blind and Low-vision Viewers Read More +
Brian Lin, Field Sales Engineer at Advantech, demonstrates the company’s latest edge AI and vision technologies and products at the 2024 Embedded Vision Summit. Specifically, Lin demonstrates his company’s edge AI vision solution embedded with NVIDIA Jetson platforms. Lin demonstrates how Advantech’s industrial cameras, equipped with Overview’s deep-learning software, effortlessly capture even the tiniest defects
Advantech Demonstration of AI Vision with an Edge AI Camera and Deep Learning Software Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Traditional video analytics applications and their development workflow are typically built on fixed-function, limited models that are designed to detect and identify only a select set of predefined objects. With generative AI, NVIDIA NIM microservices, and foundation
Build VLM-powered Visual AI Agents Using NVIDIA NIM and NVIDIA VIA Microservices Read More +
This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Large-scale, use–case-specific synthetic data has become increasingly important in real-world computer vision and AI workflows. That’s because digital twins are a powerful way to create physics-based virtual replicas of factories, retail spaces, and other assets, enabling precise simulations
Enhance Multi-camera Tracking Accuracy by Fine-tuning AI Models with Synthetic Data Read More +
Kambiz Khalilian, Director of Strategic Initiatives and Ecosystem Alliances for Lattice Semiconductor, demonstrates the company’s latest edge AI and vision technologies and products at the 2024 Embedded Vision Summit. Specifically, Khalilian demonstrates a low-latency edge AI sensor bridge solution for NVIDIA’s Holoscan. The Lattice FPGA-based Holoscan Sensor Bridge enables high-throughput and low-latency sensor aggregation and
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