Edge AI system developers often assume that AI workloads require a GPU or NPU. But when cost, latency, complex I/O or tight power budgets dominate, FPGAs offer compelling advantages.

In this talk we’ll explore how FPGA serve not just a compute block, but as a system-integration and acceleration platform that can combine tailored sensor I/O, signal processing, pre/post-processing and neural inference on one device.

We’ll also show how to map AI models onto FPGAs without doing customer hardware design, using two two practical on-ramps—(1) a software-first flow that generates custom instructions callable from C, and (2) a turnkey CNN acceleration block.

Using representative embedded-vision workloads, we’ll show apples-to-apples benchmarks. Attendees will leave with a decision checklist and a concrete “first experiment” plan.

Mark Oliver is an industry veteran with extensive experience in engineering, applications, and marketing. A native of the UK, Mark gained a degree in Electrical and Electronic Engineering from the University of Leeds. During a ten year tenure with Hewlett Packard, he managed Engineering and Manufacturing functions in HP Divisions both in Europe and the US before heading up Product Marketing and Applications Engineering at a series of video related startups. Prior to joining Efinix, Mark was Director of Worldwide Storage Accounts at Marvell, heading up Marketing and Business Development activities.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Highlights Compelling Advantages of FPGAs appeared first on Edge AI and Vision Alliance.

The Ocean Cleanup is on a mission to rid the world’s oceans of plastic. To do that, the team needs to know where plastic accumulates, how it moves, and how their cleanup systems behave in tough, remote marine environments. In this webinar, you’ll learn how they have developed and used their Autonomous Debris Imaging System (ADIS), using edge AI and computer vision to turn raw images of the ocean into useful information—right where the data is captured.

The session begins with their original monitoring setup, built with off‑the‑shelf GoPro cameras and removable hard drives. That first‑generation system validated ideas but exposed pain points: manual data collection, huge amounts of unstructured video, unreliable operation at sea and an approach that was hard to scale.

From there, Robin de Vries (The Ocean Cleanup) will walk through the second‑generation solution: a customized smart camera platform that runs computer vision models on the device. You’ll learn how the team designed a system that can handle marine conditions, work with limited connectivity and track plastic and system behavior in real time. Robin will also share challenges—hardware choices, power and thermal limits, model deployment and remote management—and the tradeoffs and lessons learned in moving from GoPros to production‑ready smart cameras.

You’ll hear about the results they’re seeing, how ADIS is changing daily operations and what’s on their roadmap.

This webinar features Robin de Vries, ADIS (Autonomous Debris Imaging System) Lead at The Ocean Cleanup. From his background in Aerospace Engineering, Geoscience, and Remote Sensing, Robin helps design and build the edge‑based monitoring systems that support large‑scale plastic cleanup. He works across hardware, software, and data to turn operational needs into embedded solutions that can run for long periods in demanding conditions and has been closely involved in the shift from GoPros to today’s smart camera platforms.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Examines Autonomous Imaging for Environmental Cleanup appeared first on Edge AI and Vision Alliance.

Running AI inference at the edge, versus in the cloud, has many compelling benefits; greater privacy, lower latency and real-time responsiveness key among them. But implementing edge AI in highly cost-, power-, or size-constrained devices has historically been impractical due to its compute, memory and storage implementation requirements.

Nowadays, however, the AI accelerators and related resources included in modern microcontrollers, in combination with technology developments and toolset enhancements that shrink the size of deep learning models, are making it possible to run computer vision, speech interfaces, and other AI capabilities at the edge.

In this webinar, Tom Hackenberg, Principal Analyst for Computing at the Yole Group, will explain that while scaling AI upward into massive data centers may dominate today’s headlines, scaling downward to edge applications may be even more transformative. Hackenberg will share market size and forecast data, along with supplier product and developer application case study examples, to support his contention that edge deployment is key to unlocking AI’s full potential across industries. A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Edge AI-enabled Microcontroller Capabilities and Trends appeared first on Edge AI and Vision Alliance.

Infrared (IR) cameras are increasingly finding adoption in a diversity of applications, as an adjunct or alternative to visible light cameras. Their ability to detect and measure energy below the visible light region of the electromagnetic spectrum makes them useful even after dark, for example, as thermal imagers, sensing objects (and their movements) whose temperatures differ from that of the ambient environment. Infrared light can also penetrate materials which visible light cannot, such as dust, fog, smoke, and thin walls. Combining visible light and infrared data results in a richer multispectrum understanding of a scene.

The infrared spectrum subdivides into short-wave (SWIR), mid-wave (MWIR) and long-wave (LWIR) regions, each with unique associated sensor implementation technologies. And both uncooled and cryogenically cooled sensor subsystems, with unique tradeoffs, contend for market acceptance. This webinar, presented by Axel Clouet, Ph.D., senior market and technology analyst for imaging at the Yole Group, will discuss the history, current status and technology and market trends for the IR imaging ecosystem, including comparisons with alternative imaging approaches. He will cover both high-margin applications such as military and surveillance and high-volume opportunities like automotive and consumer electronics, and will share Yole’s latest market forecasts. A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Infrared Image Sensor Trends and Applications appeared first on Edge AI and Vision Alliance.

It’s clear that the number of sensors per vehicle—and the sophistication of these sensors—is growing rapidly, largely thanks to increased adoption of advanced safety and driver assistance features. In this webinar, Riches will explore likely future demand for automotive radars, cameras and LiDARs.

Riches will examine which advanced driver assistance (ADAS) features will drive demand beyond 2030, how vehicle architecture change is impacting the market and what sorts of compute platforms these sensors will connect to. He will also share his firm’s vision of the autonomous vehicle landscape, considering scenarios for various automated driving levels and the resulting sensor demand. A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Sensing Solutions for ADAS and Autonomous Vehicles appeared first on Edge AI and Vision Alliance.

The CMOS image sensor (CIS) market, which is projected to grow at a 4.7% compound annual growth rate from 2023 to 2029, growing to $28.6 billion, is undergoing a transformation. Declining smartphone sales, along with weakening demand in devices such as laptops and tablet computers, are key challenges to growth.

The Yole Group forecasts that automotive cameras and other emerging applications will instead be the key drivers of future CIS market growth. Technology innovations such as triple-stacked architectures and single-photon avalanche diode-based sensors are improving performance, enabling new applications in low light and 3D imaging, for example, while high dynamic range and LED flicker mitigation are key requirements for automotive image sensors.

This webinar, co-presented by the Yole Group’s Florian Domengie, Principal Analyst for Imaging, and Anas Chalak, Technology and Market Analyst for Imaging, will discuss how CIS suppliers are focusing on enhancing sensor capabilities, along with shifting their product mixes towards higher potential value markets. Domengie and Chalak will also explore how emerging sensing modalities such as neuromorphic, optical metasurfaces, short-wave infrared and multispectral imaging will supplement, and in some cases supplant, CMOS image sensors in the future. A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores CMOS Image Sensor Trends and Applications appeared first on Edge AI and Vision Alliance.

The past decade has seen incredible progress in practical computer vision. Thanks to deep learning, computer vision is dramatically more robust and accessible, and has enabled compelling capabilities in thousands of applications, from automotive safety to healthcare.

But today’s widely used deep learning techniques suffer from serious limitations. Often, they struggle when confronted with ambiguity (e.g., are those people fighting or dancing?) or with challenging imaging conditions (e.g., is that shadow in the fog a person or a shrub?). And, for many product developers, computer vision remains out of reach due to the cost and complexity of obtaining the necessary training data, or due to lack of necessary technical skills.

Surprisingly, recent advances in large language models (and their close cousins, vision language models, which comprehend both images and text) hold the key to overcoming these challenges. Join us for this exciting expert-led 90-minute online symposium where you will learn:

• What are vision language models, and how do they combine language and vision to create a unified representation?
• What enables vision language models to generalize more effectively compared with classical vision models?
• How can product developers leverage vision language models to reduce the need for training data for new vision applications?

The symposium will feature brief presentations from three expert speakers—István Fehérvári, Director of Data and ML at BenchSci, Carter Maslan, CEO of Camio, and Jeff Bier, Founder of the Edge AI and Vision Alliance and President of BDTI—followed by a Q&A session.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Online Symposium Explores LLMs and VLMs for Computer Vision appeared first on Edge AI and Vision Alliance.

SiMa.ai has redefined AI at the Edge. With software designed to ingest and accelerate any ML model in any modality from any framework, SiMa.ai MLSoC silicon provides One Platform, purpose-built for Edge AI by enabling complete edge-ML application-pipeline acceleration on a single chip. Delivering data-center-class 50 TOPS performance with leading-edge power efficiency, and targeting applications such as industrial, retail, and healthcare, SiMa MLSoC accelerates deep learning workloads through a silicon-plus-software approach, streamlining the creation and deployment of intelligent edge AI solutions.

This webinar details the unique architecture of the SiMa.ai MLSoC, highlighting how it overcomes traditional computing limitations, and describes the capabilities of the associated toolset:

• The ModelSDK, which simplifies model loading, quantization and compilation in Python
• Python APIs and VSCode remote execution for rapid application development and prototyping
• GStreamer plugins that enable high-performance video processing pipelines
• ML Pipeline Package (MPK) tools that allow for application deployment similar to that used with mobile apps

Multiple live demonstrations will illustrate in detail the concepts presented in the webinar, and a question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Delivering High Performance and Low Power Edge AI Applications appeared first on Edge AI and Vision Alliance.

On September 26, 2024 at 9 am PT (noon ET), Jakub Pietrzak, Chief Technology Officer for SKY ENGINE AI, will present the free hour webinar “Leveraging Synthetic Data for Real-time Visual Human Behavior Analysis Using the SKY ENGINE AI Platform,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page:

Human-related applications of computer vision and AI are growing rapidly in both number and diversity. From medicine to retail to manufacturing and security, AI-powered solutions will soon be ubiquitous in our lives. In the midst of this flux, one constant remains: the need for high-quality deep learning model training data. Face and body analysis-related use cases such as face recognition and segmentation, gaze estimation and facial expression analysis make this requirement even more critical.

Training with manually-labeled real-world images has historically been the most common approach. However, this approach has multiple drawbacks, including:

• Legal and ethical concerns
• Labeling accuracy issues
• Low-diversity datasets
• Context bias
• A lack of 3D information in ground truth

These obstacles are often difficult or impossible to eliminate. SKY ENGINE AI’s approach leverages synthetic data to train computer vision models, providing an alternative methodology that bypasses these issues, and that offers support for different modalities including visible light, near infrared, radar and lidar.

In this webinar, Pietrzak will explain how 3D generative AI combines with physically-based rendering to train deep learning models for the analysis of human faces, bodies and behavior. He will also demonstrate example datasets created in the SKY ENGINE AI Synthetic Data Cloud, along with inference results from models trained purely on synthetic data. A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Synthetic Data for Deep Learning Model Training appeared first on Edge AI and Vision Alliance.

For over 30 years BDTI has provided engineering, evaluation and advisory services to processor suppliers and companies that use processors in products. We’ve seen a lot, including some classic mistakes. (You know, things like: the chip has an accelerator, but no easy way to program it… or you can only program it using an obscure proprietary framework. Or the development tools promise a lot but fall far short. Or the device drivers don’t work. Or or or … you get the idea.)

Join Lapsley for a fun and fast-paced review of some of the most common processor provider errors, ones we’ve seen repeatedly at BDTI. If you’re a processor provider, you’ll learn things you can do to avoid these goofs—and if you’re a processor user, you’ll learn about things to watch for when selecting your next processor! A question-and-answer session will follow the presentation.

To register for this free webinar, please see the event page. For more information, please email webinars@edge-ai-vision.com.

The post Free Webinar Explores Processor Evaluation and Selection appeared first on Edge AI and Vision Alliance.