In this talk, we’ll discuss emerging trends in generative AI for edge devices and the key role of transformer-based neural networks. We’ll review the distinct attributes of transformers, their advantages over conventional convolutional neural networks and how they enable generative […]
Sony’s unique integrated sensor-processor technology is enabling ultra-efficient intelligence directly at the image source, transforming vision AI for enterprises and developers alike. In this session, we’ll showcase how the AITRIOS platform simplifies vision AI for enterprises with tools for large-scale […]
In this presentation we’ll show how developers new to AI can quickly and easily create embedded vision solutions that extract valuable information from camera streams. We’ll begin by explaining how to set up the Network Optix server, client and AI […]
OAAX, an open accelerator compatibility standard being developed under the Linux Foundation AI & Data project, is key to making AI vision truly hardware-agnostic. In this talk we will highlight recent progress and our vision for seamless interoperability across CPUs, […]
In this talk, we’ll explore the evolution of multimedia processing at the edge, from simple early use cases such as audio and video processing powered by algorithm-centric approaches to modern sophisticated capabilities such as digital human avatars that are transmitted […]
As depth sensing and computer vision technologies evolve, integrating RGB and depth cameras has become crucial for reliable and precise scene perception. In this session, we present an approach for aligning images from an RGB camera with depth maps from […]
The integration of discrete AI accelerators with edge processors is poised to revolutionize the capabilities of edge computing, enabling real-time, low-latency and energy-efficient AI applications. As the computational power required for complex AI workloads increases, edge computing applications processors can […]
In this presentation, we’ll provide practical guidance on overcoming key challenges in deploying AI at the edge, including remotely managing containerized models in resource-constrained environments using scalable, purpose-built infrastructure. We’ll also cover selecting and integrating the right hardware and software […]
When building AI-powered embedded vision solutions, training and deploying AI models is just the beginning. Once deployed, engineers must continuously monitor model behavior to ensure expected performance. However, real-time visibility into model accuracy and behavior in production remains a major […]
Embedded vision applications, with their demand for ever more processing power, have been driving up the size and complexity of edge SoCs. Heterogeneous architectures that bring together CPUs, GPUs and specialized NPUs have become the standard approach to achieving high-performance […]
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