Resources
In-depth information about the edge AI and vision applications, technologies, products, markets and trends.
The content in this section of the website comes from Edge AI and Vision Alliance members and other industry luminaries.
All Resources
Microchip Advances Edge AI Sensor Connectivity with Rev 2.0 PolarFire® FPGA Ethernet Sensor Bridge
h3>Smaller, multi-camera platform enables scalable Ethernet architectures for NVIDIA Edge AI systems while lowering power, cost and integration complexity CHANDLER, Ariz., August 11, 2026 — The shift toward compact, high‑performance edge AI systems is redefining sensor
“Understanding Transformers: From LLMs to Context-Aware Multimodal Models,” a Presentation from Synopsys
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
Your NPU Learned to Listen
Whisper runs end-to-end on Chimera. Encoder and decoder compiled as native GPNPU kernels, INT4 weights, FP16 attention, top-1 token match against the float32 reference. Scales to four cores with a flag, no recompile. This
NVIDIA Alpamayo 2 Super, the Frontier Open Model for Robotaxis and Autonomous Vehicles, Now Available for Commercial Use
Open commercial licensing, benchmark‑leading reasoning and inspectable decisions bring autonomous vehicles, including robotaxis, closer to production and widescale deployment. This news blog was originally published at NVIDIA’ website. It is reprinted here with the
“Exploring Radar SLAM: Advancing Localization and Mapping for Automotive, Robotics and Beyond,” a Presentation from Cadence
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 Edge LLM Offload Story: How Synaptics Torq™ Enables High-Efficiency Gemma™ Inference
This blog post was originally published at Synaptics’ website. It is reprinted here with the permission of Synaptics. Developers and system architects today face a growing demand to enable large language model variants on device. They
Intel Releases OpenVINO 2026.3 with Expanded Generative AI and Model Support
Intel has released OpenVINO 2026.3, updating its open-source AI inference toolkit with broader model support, new generative AI pipelines, memory-efficiency improvements and expanded hardware compatibility. The release adds support for SmolLM3-3B, LFM2-1.2B and LFM2.5-1.2B across
“Vision-Language Models in Practice: Architecture and Performance,” a Presentation from AMD
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
What are the Key Engineering Challenges in Autonomous Docking Systems and How are they Solved? (Part 2)
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Designing an ROS 2-based autonomous docking system is only half the story. Deploying it in the
Technologies
Microchip Advances Edge AI Sensor Connectivity with Rev 2.0 PolarFire® FPGA Ethernet Sensor Bridge
h3>Smaller, multi-camera platform enables scalable Ethernet architectures for NVIDIA Edge AI systems while lowering power, cost and integration complexity CHANDLER, Ariz., August 11, 2026 — The shift toward compact, high‑performance edge AI systems is redefining sensor connectivity, pushing developers to deliver power‑ and space‑efficient architectures that remain secure, scalable and future‑ready. To address these challenges, Microchip
“Understanding Transformers: From LLMs to Context-Aware Multimodal Models,” a Presentation from Synopsys
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
Your NPU Learned to Listen
Whisper runs end-to-end on Chimera. Encoder and decoder compiled as native GPNPU kernels, INT4 weights, FP16 attention, top-1 token match against the float32 reference. Scales to four cores with a flag, no recompile. This blog post was originally published at Quadric’s website. It is reprinted here with the permission of Quadric. I ran a
Applications
NVIDIA Alpamayo 2 Super, the Frontier Open Model for Robotaxis and Autonomous Vehicles, Now Available for Commercial Use
Open commercial licensing, benchmark‑leading reasoning and inspectable decisions bring autonomous vehicles, including robotaxis, closer to production and widescale deployment. This news blog was originally published at NVIDIA’ website. It is reprinted here with the permission of NVIDIA. For robotaxis and other autonomous vehicles (AVs), the hardest problems aren’t the everyday scenarios. They’re the rare, complex situations that
“Exploring Radar SLAM: Advancing Localization and Mapping for Automotive, Robotics and Beyond,” a Presentation from Cadence
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
What are the Key Engineering Challenges in Autonomous Docking Systems and How are they Solved? (Part 2)
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Designing an ROS 2-based autonomous docking system is only half the story. Deploying it in the real world is another matter entirely. Since real industrial environments don’t cooperate with textbook assumptions, understanding these challenges will help
Functions
BrainChip Demonstration of the Company’s Always-On Radar-Based Edge Classification
Ritik Shrivastava, Solutions Architect at BrainChip, demonstrates Akida micro-doppler radar classification, a powerful radar-based object classification solution that runs entirely on-device without internet connection. Shrivastava showcases a live demo using BrainChip’s AKD1500 card attached to a Raspberry Pi, where the system detects and classifies between a bird and drone target in real time using radar.
AI On: 3 Ways to Bring Agentic AI to Computer Vision Applications
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Learn how to integrate vision language models into video analytics applications, from AI-powered search to fully automated video analysis. Today’s computer vision systems excel at identifying what happens in physical spaces and processes, but lack the abilities to explain the
SAM3: A New Era for Open‑Vocabulary Segmentation and Edge AI
Quality training data – especially segmented visual data – is a cornerstone of building robust vision models. Meta’s recently announced Segment Anything Model 3 (SAM3) arrives as a potential game-changer in this domain. SAM3 is a unified model that can detect, segment, and even track objects in images and videos using both text and visual
