This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our new blueprint for enabling our partners and end customers to bring more smarts to the edge was one of the highlights of Investor Day Everything around us is either already a lot smarter or aiming to […]
Qualcomm Technologies’ IoT Strategy: A New Approach, a New Opportunity Read More +
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. In Part 1 of this series we introduced you with the top 4 issues you are likely to encounter in agriculture related datasets for object detection: occlusion, label quality, data imbalance and scale variation. In Part 2
Top 4 Computer Vision Problems & Solutions in Agriculture — Part 2 Read More +
This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. Each advancement in artificial intelligence (AI), machine learning (ML), and contemporary large language models (LLMs), rekindles debates over the technological singularity, a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible,
On the Brink of the Technological Singularity: Is AI Set to Surpass Human Intelligence? Read More +
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Autonomous vehicles, such as warehouse robots, rely on precise maneuvering. NVIDIA Jetson AGX Orin™-powered surround-view cameras provide a perfectly synchronized solution, allowing these robots to move freely within designated areas without requiring intensive manual intervention.
How NVIDIA Jetson AGX Orin Helps Unlock the Power of Surround-view Camera Solutions Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. In this blog post, we take a closer look at chunked prefill, a feature of NVIDIA TensorRT-LLM that increases GPU utilization and simplifies the deployment experience for developers. This builds on our previous post discussing how advanced
This blog post was originally published at eInfochips’ website. It is reprinted here with the permission of eInfochips. Over the past several years, with strong advances in technology, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have become available in highly compact chipsets. These chipsets have been adopted across vision solutions including low power wearable
Developing and Deploying Vision-based Multi-camera Solutions Read More +
This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. Imagine you’re a developer on your first day at a new job. You’re handed a state-of-the-art sensor designed to capture data for an autonomous vehicle. The excitement quickly turns to anxiety as you realize the
Synthetic Data is Revolutionizing Sensor Tech: Real Results from Virtual Worlds Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Qualcomm Technologies sets new standards in AI performance for its latest mobile, automotive and Qualcomm AI Hub advancements Our annual Snapdragon Summit wrapped up with exciting new announcements centered on the future of on-device artificial intelligence (AI).
Snapdragon Summit’s AI Highlights: A Look at the Future of On-device AI Read More +
Vision Technology Leader Reacquired by Company’s Original Founders GALWAY, Ireland, Nov. 12, 2024– FotoNation® (www.fotonation.com), a leading provider of ultra-low power, high-efficiency computer vision AI solutions, announced that its founders have completed a management buyout of the company’s chip-level hardware, firmware, and imaging business, acquiring the company for the third time. Petronel Bigioi, its current
FotoNation Completes a Hat-trick Management Buyout Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. GPU offloading makes massive models accessible on local RTX AI PCs and workstations. Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and showcases new hardware,
How to Accelerate Larger LLMs Locally on RTX With LM Studio Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596
