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“Lessons Learned Building and Deploying a Weed-killing Robot,” a Presentation from Tensorfield Agriculture

Xiong Chang, CEO and Co-founder of Tensorfield Agriculture, presents the “Lessons Learned Building and Deploying a Weed-Killing Robot” tutorial at the May 2025 Embedded Vision Summit. Agriculture today faces chronic labor shortages and growing challenges around herbicide resistance, as well as consumer backlash to chemical inputs. Smarter, more sustainable approaches are needed to secure the […]

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Artificial Intelligence (AI) As the Semiconductor Growth Engine: AI White Paper Volume 1 – Memory & Computing

This market research report was originally published at the Yole Group’s website. It is reprinted here with the permission of the Yole Group. Yole Group Launches its First AI White Paper. KEY TAKEAWAYS Compute at the limit: Training and inference workloads now demand gigawatts of electricity, raising urgent questions on sustainability, cost, and infrastructure capacity.

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Vision Components Presents VC MIPI Multiview Cam: MIPI CSI-2-based Camera for Light Field Measurement and Multispectral Imaging

VC MIPI Multiview Cam is a new OEM module for light field measurements, multiview and multispectral imaging from Vision Components. It can be connected to common processor boards via a single MIPI CSI-2 interface. Ettlingen, October 09, 2025.  Vision Components is expanding its product range with the VC MIPI Multiview Cam, a camera array with

Vision Components Presents VC MIPI Multiview Cam: MIPI CSI-2-based Camera for Light Field Measurement and Multispectral Imaging Read More +

Using the Qualcomm AI Inference Suite from Google Colab

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Building off of the blog post here, which shows how easy it is to call the Cirrascale AI Inference Cloud using the Qualcomm AI Inference Suite, we’ll use Google Colab to show the same scenario. In the previous blog

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“Transformer Networks: How They Work and Why They Matter,” a Presentation from Synthpop AI

Rakshit Agrawal, Principal AI Scientist at Synthpop AI, presents the “Transformer Networks: How They Work and Why They Matter” tutorial at the May 2025 Embedded Vision Summit. Transformer neural networks have revolutionized artificial intelligence by introducing an architecture built around self-attention mechanisms. This has enabled unprecedented advances in understanding sequential data, such as human languages,

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How Do Speed Cameras Make the Roads Safer?

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Speed cameras play a crucial role in promoting safer roads. They can detect, capture, and record instances of speeding. Get insights into how these cameras work and their major road safety use cases. Managing road

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“Virtual Reality, Machine Learning and Biosensing Advances Converging to Transform Healthcare and Beyond,” an Interview with Stanford University

Walter Greenleaf, Neuroscientist at Stanford University’s Virtual Human Interaction Lab, talks with Tom Vogelsong, Start-Up Scout at K2X Technology and Life Science for the “Virtual Reality, Machine Learning and Biosensing Advances Converging to Transform Healthcare and Beyond” interview at the May 2025 Embedded Vision Summit. In this wide-ranging interview, Greenleaf explains how advances in virtual

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Qualcomm to Acquire Arduino—Accelerating Developers’ Access to its Leading Edge Computing and AI

New Arduino UNO Q and Arduino App Lab to Enable Millions of Developers with the Power of Qualcomm Dragonwing Processors Highlights: Acquisition to combine Qualcomm’s leading-edge products and technologies with Arduino’s vast ecosystem and community to empower businesses, students, entrepreneurs, tech professionals, educators and enthusiasts to quickly and easily bring ideas to life. New Arduino

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Deploy High-performance AI Models in Windows Applications on NVIDIA RTX AI PCs

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Microsoft is now making Windows ML available to developers. Windows ML enables C#, C++ and Python developers to optimally run AI models locally across PC hardware from CPU, NPU and GPUs. On NVIDIA RTX GPUs, it utilizes

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“Understanding Human Activity from Visual Data,” a Presentation from Sportlogiq

Mehrsan Javan, Chief Technology Officer at Sportlogiq, presents the “Understanding Human Activity from Visual Data” tutorial at the May 2025 Embedded Vision Summit. Activity detection and recognition are crucial tasks in various industries, including surveillance and sports analytics. In this talk, Javan provides an in-depth exploration of human activity understanding, covering the fundamentals of activity

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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.

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