Software for Embedded Vision
Make Your Existing NVIDIA Jetson Orin Devices Faster with Super Mode
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. The NVIDIA Jetson Orin Nano Super Developer Kit, with its compact size and high-performance computing capabilities, is redefining generative AI for small edge devices. NVIDIA has dropped an exciting new update to their existing Jetson
Empowering Civil Construction with AI-driven Spatial Perception
This blog post was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Transforming Safety, Efficiency, and Automation in Construction Ecosystems In the rapidly evolving field of civil construction, AI-based spatial perception technologies are reshaping the way machinery operates in dynamic and unpredictable environments. These systems enable advanced
Can Money Buy AI Dominance?
This market research report was originally published at the Yole Group’s website. It is reprinted here with the permission of the Yole Group. The announcements of the creation of Stargate last week as well as the revelation of DeepSeek-V3’s performance at a much lower cost than OpenAI and its competitors are both raising a lot
The Future of AI in Business: Trends to Watch
This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. In a world increasingly shaped by the rapid evolution of artificial intelligence, 2024 stands as another momentous year, with advancements that continue to reshape how we live, work, and imagine our future. From the rapid acceleration in
Multimodal Large Language Models: Transforming Computer Vision
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. This article introduces multimodal large language models (MLLMs) [1], their applications using challenging prompts, and the top models reshaping computer vision as we speak. What is a multimodal large language model (MLLM)? In layman terms, a multimodal
How Qualcomm is Catalyzing Retail’s AI Revolution
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Retail is embracing innovation — we’ll be showing off examples of these game-changing experiences at NRF 2025 With more places to shop than ever, physical stores are turning to AI and technology for a competitive edge. That
How Au-Zone Technologies Plays a Key Role in the Ocean Cleanup Automated Debris Imaging System
This blog post was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Founded in 2012 in Rotterdam, The Netherlands, The Ocean Cleanup is developing and scaling technologies to rid the oceans of plastic with ocean cleanup systems and river interception technologies. With over 150 employees, The Ocean
DALL-E vs Gemini vs Stability: GenAI Evaluations
This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. We performed a side-by-side comparison of three models from leading providers in Generative AI for Vision. This is what we found: Despite the subjectivity involved in Human Evaluation, this is the best approach to evaluate state-of-the-art GenAI Vision
Harnessing the Power of LLM Models on Arm CPUs for Edge Devices
This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. In recent years, the field of machine learning has witnessed significant advancements, particularly with the development of Large Language Models (LLMs) and image generation models. Traditionally, these models have relied on powerful cloud-based infrastructures to deliver impressive
AI On the Road: Why AI-powered Cars are the Future
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. AI transforms your driving experience in unexpected ways as showcased by Qualcomm Technologies collaborations As automotive technology rapidly advances, consumers are looking for vehicles that deliver AI-enhanced experiences through conversational voice assistants and sophisticated user interfaces. Automotive
CPUs, GPUs, and AI: Exploring High-performance Computing Hardware
IDTechEx‘s latest report, “Hardware for HPC and AI 2025-2035: Technologies, Markets, Forecasts“, provides data to show that the use of graphics processing units (GPUs) within high performance computing (HPC) has been increasingly adopted since the introduction of generative AI and large language models, as well as advanced memory, storage, networking, and cooling technologies. Drivers for
Visual Intelligence at the Edge
This blog post was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Optimizing AI-based video telematics deployments on constrained SoCs platforms The demand for advanced video telematics systems is growing rapidly as companies seek to enhance road safety, improve operational efficiency, and manage liability costs with AI-powered
NVIDIA JetPack 6.2 Brings Super Mode to NVIDIA Jetson Orin Nano and Jetson Orin NX Modules
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The introduction of the NVIDIA Jetson Orin Nano Super Developer Kit sparked a new age of generative AI for small edge devices. The new Super Mode delivered an unprecedented generative AI performance boost of up to 1.7x
Improving Vision Model Performance Using Roboflow and Tenyks
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. When improving an object detection model, many engineers focus solely on tweaking the model architecture and hyperparameters. However, the root cause of mediocre performance often lies in the data itself. In this collaborative post between Roboflow and
Federated Learning: Risks and Challenges
This blog post was originally published at Digica’s website. It is reprinted here with the permission of Digica. In the first article of our mini-series on Federated Learning (FL), Privacy-First AI: Exploring Federated Learning, we introduced the basic concepts behind the decentralized training approach, and we also presented potential applications in certain domains. Undoubtedly, FL
Edge Intelligence and Interoperability are the Key Components Driving the Next Chapter of the Smart Home
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. The smart home industry is on the brink of a significant leap forward, fueled by generative AI and edge capabilities The smart home is evolving to include advanced capabilities, such as digital assistants that interact like friends
Accelerate Custom Video Foundation Model Pipelines with New NVIDIA NeMo Framework Capabilities
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Generative AI has evolved from text-based models to multimodal models, with a recent expansion into video, opening up new potential uses across various industries. Video models can create new experiences for users or simulate scenarios for training
NVIDIA TAO Toolkit: How to Build a Data-centric Pipeline to Improve Model Performance (Part 3 of 3)
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. During this series, we will use Tenyks to build a data-centric pipeline to debug and fix a model trained with the NVIDIA TAO Toolkit. Part 1. We demystify the NVIDIA ecosystem and define a data-centric pipeline based
