AWS Physical AI Blog

Dario Macagnano

Author: Dario Macagnano

is a Physical AI Solutions Architect at AWS. With years of experience designing and deploying solutions spanning real-time simulation, digital twins, and edge inference — from rapid prototypes to large-scale production systems — Dario is passionate about the convergence of AI, robotics, and cloud infrastructure that brings intelligent systems into the physical world.

Rendering Digital Humans with Amazon EC2 Spot Instances

Amazon Web Services would like to thank the UneeQ Engineering team for their contribution to this post Introduction UneeQ creates AI-powered digital humans that engage in natural conversations while displaying realistic facial expressions through real-time high-fidelity 3D rendering. Running these compute-intensive workloads, built on game engines like Unreal Engine, is inherently complex. That complexity multiplies […]

Flexible Manufacturing with AWS and SoftServe: How Simulation-First Robotics Reaches Production Faster

Introduction Manufacturers need automation that adapts to changing products without costly rework. At Hannover Messe 2026, SoftServe and AWS demonstrated a simulation-first approach to flexible robotic manufacturing, powered by AWS cloud services for AI orchestration, IoT communication, and quality inspection that ran continuously for five days with a near-100 percent pick success rate during live […]

Sim-to-Real and Real-to-Sim: The Engine Behind Capable Physical AI

Introduction Physical AI systems – robots that perceive, reason, and act in the real world, are advancing rapidly. The Sim-to-Real pipeline is at the heart of this progress. However, building models that work reliably outside the lab remains one of the hardest problems in the field. The gap between what works in simulation and what […]