Software for Embedded Vision
DeGirum Demonstration of Its PySDK Running on BrainChip Hardware for Real-time Edge AI
Stephan Sokolov, Software Engineer at DeGirum, demonstrates the company’s latest edge AI and vision technologies and products in BrainChip’s booth at the 2025 Embedded Vision Summit. Specifically, Sokolov demonstrates the power of real-time AI inference at the edge, running DeGirum’s PySDK application directly on BrainChip hardware. This demo showcases low-latency, high-efficiency performance as a script
Best-in-class Multimodal RAG: How the Llama 3.2 NeMo Retriever Embedding Model Boosts Pipeline Accuracy
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Data goes far beyond text—it is inherently multimodal, encompassing images, video, audio, and more, often in complex and unstructured formats. While the common method is to convert PDFs, scanned images, slides, and other documents into text, it
BrainChip Demonstration of LLM Inference On an FPGA at the Edge using the TENNs Framework
Kurt Manninen, Senior Solutions Architect at BrainChip, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Van Manninen demonstrates his company’s large language models (LLMs) running on an FPGA edge device, powered by BrainChip’s proprietary TENNs (Temporal Event-Based Neural Networks) framework. BrainChip enables real-time generative AI
BrainChip Demonstration of Its Latest Audio AI Models in Action At the Edge
Richard Resseguie, Senior Product Manager at BrainChip, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Van Resseguie demonstrates the company’s latest advancements in edge audio AI. The demo features a suite of models purpose-built for real-world applications including automatic speech recognition, denoising, keyword spotting, and
Network Optix Demonstration of How the Company is Powering Scalable Data-driven Video Infrastructure
Tagir Gadelshin, Director of Product at Network Optix, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Gadelshin demonstrates how the company’s latest release, Gen 6 Enterprise, is enabling cloud-powered, event-driven video infrastructure for enterprise organizations at scale. Built on Nx EVOS, Gen 6 Enterprise supports
Network Optix Demonstration of Seamless AI Model Integration with Nx AI Manager
Robert van Emdem, Senior Director of Data Science at Network Optix, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Van Emdem demonstrates how Nx AI Manager enables seamless deployment of AI models across a wide variety of hardware, including GPU, VPU, and CPU environments. van
Small Purpose Built AI Models
This blog post was originally published at Synetic AI’s website. It is reprinted here with the permission of Synetic AI. In an era dominated by ever-larger foundation models, a quieter revolution is underway—one defined not by scale, but by precision. This paper argues that the most impactful AI systems of the future will not be
Network Optix Demonstration of Extracting AI Model Data with AI Manager
Marcel Wouters, Senior Backend Engineer at Network Optix, the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Wouters demonstrates how Nx AI Manager simplifies the extraction and use of data from AI models. Wouters showcases a live model detecting helmets and vests on a construction site and
Network Optix Overview of the Company’s Technologies, Products and Capabilities
Bradley Milligan, North America Sales Coordinator at Network Optix, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Milligan shares how Network Optix is enabling scalable, intelligent video solutions for organizations and industries around the world, including by using Nx EVOS and Nx AI Manager. Learn
Qualcomm Trends and Technologies to Watch In IoT and Edge AI
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. “It’s amazing how Qualcomm was able to turn the ship on a dime since the last [Embedded World] show. The launch of Qualcomm Dragonwing and the Partner Day event were on point and helpful, showing Qualcomm’s commitment
Nota AI Collaborates with Renesas on High-efficiency Driver Monitoring AI for RA8P1 Microcontroller
AI model optimization powers high-efficiency DMS on ultra-compact MCUs 50FPS real-time performance with ultra-low power and minimal system footprint SEOUL, South Korea, July 2, 2025 /PRNewswire/ — Nota AI, a global leader in AI optimization, today announced a collaboration with Renesas Electronics Corporation, a premier supplier of advanced semiconductor solutions, to deliver an optimized Driver Monitoring
“Voice Interfaces on a Budget: Building Real-time Speech Recognition on Low-cost Hardware,” a Presentation from Useful Sensors
Pete Warden, CEO of Useful Sensors, presents the “Voice Interfaces on a Budget: Building Real-time Speech Recognition on Low-cost Hardware” tutorial at the May 2025 Embedded Vision Summit. In this talk, Warden presents Moonshine, a speech-to-text model that outperforms OpenAI’s Whisper by a factor of five in terms of speed.… “Voice Interfaces on a Budget:
Introducing NVFP4 for Efficient and Accurate Low-precision Inference
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. To get the most out of AI, optimizations are critical. When developers think about optimizing AI models for inference, model compression techniques—such as quantization, distillation, and pruning—typically come to mind. The most common of the three, without
“Computer Vision at Sea: Automated Fish Tracking for Sustainable Fishing,” a Presentation from Tryolabs and the Nature Conservancy
Alicia Schandy Wood, Machine Learning Engineer at Tryolabs, and Vienna Saccomanno, Senior Scientist at The Nature Conservancy, co-present the “Computer Vision at Sea: Automated Fish Tracking for Sustainable Fishing” tutorial at the May 2025 Embedded Vision Summit. What occurs between the moment a commercial fishing vessel departs from shore and… “Computer Vision at Sea: Automated
Simplifying Vision AI Development with Renesas AI Model Deployer Powered by NVIDIA TAO
This blog post was originally published at Renesas’ website. It is reprinted here with the permission of Renesas. Edge AI is no longer a futuristic idea—it’s an essential technology driving today’s smart devices across industries, from industrial automation to consumer IoT applications. But building AI applications at the edge still comes with challenges: complexity with
“Squinting Vision Pipelines: Detecting and Correcting Errors in Vision Models at Runtime,” a Presentation from Squint AI
Ken Wenger, Chief Technology Officer at Squint AI, presents the “Squinting Vision Pipelines: Detecting and Correcting Errors in Vision Models at Runtime” tutorial at the May 2025 Embedded Vision Summit. As humans, when we look at a scene our first impressions are sometimes wrong; we need to take a second… “Squinting Vision Pipelines: Detecting and
The Outer Loop: The Real Driver of AI Success
This blog post was originally published in expanded form at RapidFire AI’s website. It is reprinted here with the permission of RapidFire AI. When people talk about deep learning, they usually talk about the inner loop—the elegant dance of forward passes, backpropagation, and gradient descent. This is the part that’s been endlessly refined over the
“ONNX and Python to C++: State-of-the-art Graph Compilation,” a Presentation from Quadric
Nigel Drego, Co-founder and Chief Technology Officer at Quadric, presents the “ONNX and Python to C++: State-of-the-art Graph Compilation” tutorial at the May 2025 Embedded Vision Summit. Quadric’s Chimera general-purpose neural processor executes complete AI/ML graphs—all layers, including pre- and post-processing functions traditionally run on separate DSP processors. To enable… “ONNX and Python to C++:
