Summit 2026

“AGI Meets the Real World—Toward Reasoning, Planning and Acting Beyond Book Intelligence,” a Presentation from Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University

Algorithms & Models, Edge AI and Vision Alliance, Summit 2026, Videos /

Eric Xing, President and Professor at Mohamed bin Zayed University of Artificial Intelligence and Carnegie Mellon University presents “AGI Meets the Real World—Toward Reasoning, Planning and Acting Beyond Book Intelligence” at the May 2026 Embedded Vision Summit. LLMs like OpenAI’s GPTs have fascinated the public with their astounding capabilities on… “AGI Meets the Real World—Toward […]

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“Self-Compression for Edge Inference,” a Presentation from Imagination Technologies

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James Imber, Director of Research at Imagination Technologies presents “Self-Compression for Edge Inference” at the May 2026 Embedded Vision Summit. Self-compression is a quantization-aware training technique to reduce neural network size and optimize performance for edge inference. By learning optimal bit depths for weights and activations during training, self-compression achieves… “Self-Compression for Edge Inference,” a

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“Introduction to Simultaneous Localization and Mapping: From Block Diagrams to Real Systems,” a Presentation from eInfochips (an Arrow company)

Algorithms & Models, Edge AI and Vision Alliance, eInfochips, Summit 2026, Videos /

Amit Gupta, Associate Director–Solution Architecture and Head of Robotics CoE at eInfochips (an Arrow company) presents “Introduction to Simultaneous Localization and Mapping: From Block Diagrams to Real Systems” at the May 2026 Embedded Vision Summit. Simultaneous localization and mapping (SLAM) is the core capability that allows robots and autonomous systems… “Introduction to Simultaneous Localization and

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“Understanding Transformers: From LLMs to Context-Aware Multimodal Models,” a Presentation from Synopsys

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Tom Michiels, System Architect at Synopsys presents “Understanding Transformers: From LLMs to Context-Aware Multimodal Models” at the May 2026 Embedded Vision Summit. Transformers have become the foundation of modern AI, reshaping how products are built and how businesses operate. In this talk Michiels explains why transformers replaced earlier models, what… “Understanding Transformers: From LLMs to

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“Exploring Radar SLAM: Advancing Localization and Mapping for Automotive, Robotics and Beyond,” a Presentation from Cadence

Algorithms & Models, Automotive, Cadence, Edge AI and Vision Alliance, Robotics, Summit 2026, Videos /

Amit Kumar, Director of Product Management and Marketing at Cadence and Amit Sulakhe, Director in the Vision Group at Cadence Pune present “Exploring Radar SLAM: Advancing Localization and Mapping for Automotive, Robotics and Beyond” at the May 2026 Embedded Vision Summit. Reliable localization and mapping are foundational for autonomous vehicles… “Exploring Radar SLAM: Advancing Localization

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“Vision-Language Models in Practice: Architecture and Performance,” a Presentation from AMD

Algorithms & Models, AMD, Edge AI and Vision Alliance, Summit 2026, Videos, VLMs /

Rajy Rawther, PMTS Software Architect at AMD presents “Vision-Language Models in Practice: Architecture and Performance” at the May 2026 Embedded Vision Summit. Unimodal vision systems are powerful but limited when users need flexible queries, richer semantics or reasoning that combines images/video with language. Vision-language models (VLMs) address this gap by… “Vision-Language Models in Practice: Architecture

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“Small Language Models for Edge AI: Trade-Offs and Quantization in Practice,” a Presentation from AMD

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Dwith Chenna, MTS Product Engineer, AI Inference at AMD presents “Small Language Models for Edge AI: Trade-Offs and Quantization in Practice” at the May 2026 Embedded Vision Summit. Large language models are powerful but often impractical for embedded and on-prem systems due to latency, cost, privacy and memory constraints. Small… “Small Language Models for Edge

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Synetic Demonstration of Synthetic Training Data for Computer Vision Edge Case Coverage

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David Scott, CEO & Founder at Synetic, makes the case for synthetic training data as the most practical solution to edge case coverage in computer vision at the 2025 Embedded Vision Summit. Real-world data collection is slow, expensive, and structurally unable to capture the rare but critical scenarios — adverse lighting, unusual occlusions, extreme environments

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Synetic Demonstration of the LYNX SDK Beta: Real-Time CV Across Six Platforms in One Call

Algorithms & Models, Summit 2026, Synetic AI, Videos /

David Scott, CEO & Founder at Synetic, demonstrates the LYNX SDK beta release at the 2026 Embedded Vision Summit. LYNX returns detection, segmentation, depth, and keypoints simultaneously from a single forward pass, eliminating the need to chain multiple models on constrained edge hardware. David highlights several capabilities shipping in the beta: 3D positioning from a

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Synetic Demonstration of the LYNX Computer Vision SDK and Synthetic Data as a Service Platform

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Will Ruffalo, Co-Founder at Synetic, introduces two of the company’s core offerings at the 2026 Embedded Vision Summit: the LYNX computer vision SDK and Synetic’s synthetic data as a service platform. LYNX delivers detection, segmentation, keypoints, and depth in a single inference call, across six platforms, from a single model artifact. Will also demonstrates how

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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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