The transformer architecture revolutionized the field of AI and serves as the basis for current state-of-the-art large language models. Yet, transformer networks struggle with the quadratic complexity of long sequences, a critical bottleneck for high-resolution embedded vision. In this talk, […]

Segmentation is fundamental to edge vision—from drivable surface detection to industrial inspection. But how do different approaches actually perform on resource-constrained hardware? This session benchmarks segmentation models across NVIDIA Jetson, NXP i.MX, Kinara NPU and Raspberry Pi with Hailo acceleration, […]

Large language models are powerful but often impractical for embedded and on-prem systems due to latency, cost, privacy and memory constraints. Small language models (SLMs)—typically comprised of single-digit billions of parameters or less—offer a deployable alternative but require different expectations […]

In safety-critical computer vision applications such as medical diagnostics and autonomous driving, corrupted training data can be fatal. A famous example involves a dermatology AI that learned to identify rulers rather than tumors, a classic case of data poisoning. This […]

Natural language video search—“find the man in the green hoodie riding a bike”—can turn a camera network from passive recording into a proactive investigation tool. But brute-force approaches fail: cloud processing of streaming video is cost- and bandwidth-prohibitive at scale, […]

Vision-language models (VLMs) enable “world understanding” tasks—natural language queries, zero-shot reasoning and richer scene context—that go beyond traditional CNN pipelines. But bringing VLMs to the edge is primarily a systems problem: selecting a model you can govern (license and data […]

Many AI medical devices perform perfectly in the lab but fail in the field, for example due to “ungradable” images in the case of retina screening. This talk details the end-to-end engineering journey of a portable, regulatory-cleared retinal camera designed […]

Obtaining suitable training data remains a core challenge in the development of custom computer vision solutions for industrial applications such as those in supply chain and logistics. Industrial data differs fundamentally from common datasets—it is often domain-specific, making it expensive […]

Software-defined vehicles and in-vehicle AI are reshaping automotive compute from dozens of distributed ECUs to centralized and zonal architectures—fundamentally changing how data movement, power delivery, safety and cost are engineered. This talk compares decentralized, centralized and zonal compute approaches and […]

Industrial visual inspection operates at the intersection of perception, decision-making and physical consequences. Despite advances in automated vision and large foundation models, industrial inspection remains fundamentally unsolved: the assets being inspected are domain-specific and evolving, labeled data is scarce, environments […]