Algorithms & Models

“From Compute-Bound to Memory-Bound: Edge AI Architectures for VLMs,” a Presentation from Expedera

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Athish Rahul Rao, Staff Software Engineer at Expedera presents “From Compute-Bound to Memory-Bound: Edge AI Architectures for VLMs” at the May 2026 Embedded Vision Summit. Today’s edge AI hardware was built for CNNs, but vision language models (VLMs) have completely different bottlenecks—especially in safety-critical, latency-sensitive applications like in-cabin automotive intelligence.… “From Compute-Bound to Memory-Bound: Edge […]

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How to Overcome Vision Challenges While Building a Multi-Robot Mapping System (Part 2)

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This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. In part 1 of this series, you explored why multi-robot autonomous mapping is becoming essential for large-scale facilities and what the core components of a modern multi-robot mapping system are. But knowing what a system should

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“Navigating Physical AI Deployment Across Multiple Platforms for Automated Optical Inspection,” a Presentation from eInfochips (an Arrow company)

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Barrie Mullins, Assistant Vice President at eInfochips (an Arrow company) presents “Navigating Physical AI Deployment Across Multiple Platforms for Automated Optical Inspection” at the May 2026 Embedded Vision Summit. As automated optical inspection moves from the server room to the factory floor, the promise of “seamless” AI deployment often hits… “Navigating Physical AI Deployment Across

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“Why Edge Vision Models Keep Breaking—and What Complete Training Data Changes,” a Presentation from Synetic

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David Scott, Founder and CEO at Synetic presents “Why Edge Vision Models Keep Breaking—and What Complete Training Data Changes” at the May 2026 Embedded Vision Summit. Most edge vision deployments fail not because of model architecture, but because real-world training data is structurally incomplete. Sampled data can’t cover combinatorial edge… “Why Edge Vision Models Keep

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Free Webinar Highlights Compelling Advantages of Synthetic Data

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On August 11, 2026 at 9 am PT (noon ET), Synetic AI’s Founder and CEO David Scott, will present the free hour webinar “Why Edge Vision Models Keep Breaking—and What Complete Training Data Changes,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: Most edge vision deployments fail

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Why Multi-Robot Autonomous Mapping Is Becoming Essential for Large-Scale Facilities (Part 1)

Algorithms & Models, Blog Posts, e-con Systems, Robotics, Software, Tools /

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. For years, facility digitization has relied on a single, expensive robot slowly traversing every corridor of a warehouse, laboratory, or industrial plant. While effective, this approach is linear, which clashes with the fact that facilities are

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“Edge AI and Vision in Robotics: From Benchmarks to Fleet-Scale Reality,” an Expert Panel

Algorithms & Models, Ambarella, Edge AI and Vision Alliance, Memory, Processors, Qualcomm, Robotics, Sensors and Cameras, Summit 2026, Tools, Videos /

Dave Tokic, Vlad Branzoi, Bob Kunz, Rajan Mistry, Durgesh Tiwari, Vice President of Corporate Development at Torc Robotics presents “Edge AI and Vision in Robotics: From Benchmarks to Fleet-Scale Reality” at the May 2026 Embedded Vision Summit. Edge AI is helping robots see, decide and act in the real world—but… “Edge AI and Vision in

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“Efficient Computer Vision at the Far Edge: Design and Training Under Constraints,” a Presentation from Lattice Semiconductor

Algorithms & Models, Edge AI and Vision Alliance, Lattice Semiconductor, Memory, Processors, Summit 2026, Videos /

Nicolas Widynski, AI Fellow at Lattice Semiconductor presents “Efficient Computer Vision at the Far Edge: Design and Training Under Constraints” at the May 2026 Embedded Vision Summit. This session explores practical strategies for deploying computer vision AI on far-edge devices under strict resource constraints. While highlighting FPGA-specific strengths, such as… “Efficient Computer Vision at the

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Running BitNet on Qualcomm Hexagon with custom 1.58 kernels

Algorithms & Models, Blog Posts, ENERZAi, Processors, Qualcomm, Tools /

This blog post was originally published at ENERZAi’s website. It is reprinted here with the permission of ENERZAi. Today, we are excited to share a milestone that our team has been working toward for some time. ENERZAi has successfully deployed BitNet (b1.58) 2B on the Qualcomm QCS6490 Hexagon NPU via QNN! If that sentence felt

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Why Vision LLMs Force A Rethink Of Edge AI Hardware

Algorithms & Models, Blog Posts, Expedera, Processors /

This blog post was originally published at Expedera’s website. It is reprinted here with the permission of Expedera. As vision-centric large language models move on-device, performance measured in raw TOPS is no longer enough. Architectures need to be built around real workloads, memory behavior, and sustained utilization, especially at the edge. Vision LLMs are changing

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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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