At dAIEDGE, we work to accelerate the adoption of Edge AI, bringing advanced models to where they really make an impact. However, optimizing AI models to run on limited hardware remains one of the main technical and strategic challenges for companies and developers.
With this goal in mind, our partner Hes-so has organized the conference “Optimize Your AI at the Edge: Explore Hardware Options with dAIEDGE-VLab,” a workshop designed to help SMEs, tech startups, researchers, and machine learning professionals make informed decisions about deploying AI on Edge devices.
The event, to be held on March 23, 2026, will offer a structured and practical overview of how to select the most appropriate hardware based on performance, power consumption, cost, and latency requirements. Through hands-on demonstrations and applied exercises, participants will learn how to evaluate different accelerators and platforms, how to interpret real execution metrics, and how to optimize models for resource-constrained environments.
A central element of the conference will be the demonstration of dAIEDGE-VLab, our virtual environment that allows you to test, compare, and analyze the performance of AI models on different hardware configurations. The goal is to provide an objective basis for technological decision-making, reducing the uncertainty that often accompanies Edge deployment. Beyond theory, we will work with benchmarks, real measurements, and practical scenarios that reflect current industrial challenges.
The conference is designed to suit different profiles. Those interested in a more strategic approach will be able to follow the conceptual sessions with their own laptop, while technical profiles will be able to participate in practical activities that require basic knowledge of Python and development environments. In both cases, the approach will be rigorous, applied, and results-oriented.
Places are limited (25) to ensure a quality experience and an environment of direct interaction with our experts. We invite all organizations and professionals interested in optimizing their Edge AI solutions to register and take part in this working session. Register by clicking here.