Edge AI and Vision Alliance@edgeaivision

Inspiring and empowering engineers to design products that perceive and understand.

 Walnut Creek, CA
edge-ai-vision.com
Joined May 2011
4,993 Photos and videos
How do you make battery-powered vision sensors practical with on-device AI? @VergeSense's Larry Arne covers power budgets, battery chemistry, memory, NPUs, switched power domains and wireless design. #EdgeAI #EmbeddedVision #LowPowerAI edge-ai-vision.com/2026/10/d…
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What kinds of robots are transforming industry and daily life? @MicronTech breaks down industrial, service, mobile, collaborative, humanoid and autonomous robots—and the AI, memory and storage enabling them. #Robotics #PhysicalAI #EdgeAI edge-ai-vision.com/2026/10/t…
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Free webinar Dec. 15: EyePop.ai, Pinterest and Velasea explore how to move computer vision from experiments to scalable production—covering composable workflows, VLMs, edge/hybrid deployment and smarter orchestration. #ComputerVision #EdgeAI edge-ai-vision.com/2026/10/f…

EyePop.ai: Detect People, Objects & Actions - Any Camera, Any Feed

Give your surveillance deployments custom AI detection — people, vehicles, behavior — without building an ML team. Works with your existing cameras and VMS. Train and deploy in hours.

eyepop.ai
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@Lincode_AI explores how predictive maintenance is evolving with edge AI, no-code model training, factory-system integration and combined visual + mechanical data to catch machine problems before they become downtime. #IndustrialAI #PredictiveMaintenance edge-ai-vision.com/2026/10/a…
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Edge AI performance depends on more than peak throughput. @Valeo’s Pullarao Maddu compares monolithic vs. decomposed AI pipelines and shows how CPUs, GPUs, NPUs, DSPs, memory traffic and scheduling shape deterministic real-time behavior. #EmbeddedAI edge-ai-vision.com/2026/10/d…
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How can developers run generative AI efficiently on local Intel hardware? This upcoming webinar explores using @OpenVINO to optimize and deploy GenAI workloads across CPUs, GPUs and NPUs. #GenerativeAI #OpenVINO #EdgeAI #OnDeviceAI edge-ai-vision.com/2026/10/u…
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How can AI agents edit images through natural language? @UWMadison and @AdobeResearch’s Yong Jae Lee explores multimodal agents that combine intent understanding, grounded region editing and multistep planning. #MultimodalAI #AgenticAI #ComputerVision edge-ai-vision.com/2026/10/m…
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Which object detector fits your application? Union.ai’s Sage Elliott compares Faster R-CNN, YOLO, SSD, MobileNet, EfficientDet and vision transformers across speed, accuracy and efficiency—especially for edge deployment. #ObjectDetection edge-ai-vision.com/2026/10/o…
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This week in Insights: better training data for edge AI, how to choose processors beyond TOPS, new AI development tools and sensing products, plus ENERZAi’s award-winning audio + language AI software. #EdgeAI #ComputerVision #PhysicalAI edge-ai-vision.com/2026/10/e…
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Why do AI models fail when conditions change? Squint Cognition explains shortcut learning as a geometry problem in latent space—and how examining representation structure can reveal brittle behavior before deployment. #AI #ComputerVision #TrustworthyAI edge-ai-vision.com/2026/10/t…
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How do you turn noisy iPhone/iPad LiDAR scans into engineering-grade building models? Twindo’s Anton Yakubenko shares lessons from 150M+ sq. ft., spanning mesh cleanup, semantic segmentation, primitive extraction and human-in-the-loop QA. #3DVision #LiDAR edge-ai-vision.com/2026/10/f…
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New to DNN training? Think Circuits CEO Kevin Weekly explains supervised, unsupervised and semi-supervised learning, backpropagation, hyperparameters, regularization, loss curves and common pitfalls like overfitting. #DeepLearning #MachineLearning #EdgeAI edge-ai-vision.com/2026/10/i…
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Working distance is more than lens-to-object spacing. Commonlands explains how working distance and minimum object distance affect focus, field of view and lens selection in machine vision systems. #MachineVision #Optics #EmbeddedVision edge-ai-vision.com/2026/10/w…
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Stereo, ToF, LiDAR—or monocular depth AI? Think Circuits’ Chris Sarantos compares depth-sensing technologies across range, resolution, frame rate, eye safety and application fit. #3DVision #DepthSensing #ComputerVision #Robotics edge-ai-vision.com/2026/10/i…
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Transformers struggle with long sequences. Tel Aviv University’s Raja Giryes explores state-space models like Mamba as a linear-complexity alternative, plus LongMamba, DeciMamba and “hidden attention” for interpretable edge AI. #EdgeAI #Mamba #SSM edge-ai-vision.com/2026/10/e…
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Can low-cost SoCs really run multimodal AI? @SuperfocusAI tested 17 chips across small LLM, speech and vision-language workloads—and found that TOPS often fails to predict real-world performance. #EdgeAI #MultimodalAI #OnDeviceAI edge-ai-vision.com/2026/10/c…
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Why are cameras becoming core to product differentiation? @eInfochips explores the shift from imaging devices to intelligent perception systems combining optics, ISP pipelines, AI and multi-camera sensing. #ComputerVision #EdgeAI #EmbeddedVision edge-ai-vision.com/2026/10/w…
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Hearing aids are becoming multifunctional edge AI platforms. @starkeyhearing CTO Achin Bhowmik explores embedded DNNs for speech enhancement, health sensing, fall detection and context-aware assistance—all under extreme power and size constraints. #EdgeAI edge-ai-vision.com/2026/10/e…
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Free webinar Oct. 8: @D3Embedded explores how cameras, thermal sensing, LiDAR and mmWave radar can work together for more reliable #PhysicalAI—covering sensor fusion, calibration, synchronization, edge processing and validation. #EdgeAI #SensorFusion edge-ai-vision.com/2026/08/f…
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AI-defined machines are replacing fixed software stacks. @Rivian’s Andy Xiao explores how autonomy, robotics and industrial systems are converging around foundation models, world models, simulation and continuous edge deployment. #PhysicalAI #EdgeAI edge-ai-vision.com/2026/10/t…
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