Category: Artificial Intelligence

Self-Driving Labs® are no longer a vision Developing a new drug takes an average of 10-15 years and costs over $2 billion. For patients waiting on life-saving treatments, every month of R&D delay matters. The bottleneck isn’t a lack of scientific talent, it’s the sheer scale of experimentation required. A single drug optimization campaign might […]

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 […]

Introduction Organizations across urban planning, emergency management, and defense need to model how populations move and behave in spatial environments. Whether simulating an evacuation, modeling resource competition, or analyzing urban migration patterns, understanding human behavior at scale is critical. Traditional agent-based models rely on hardcoded rules that produce predictable, unrealistic behavior. Generative AI changes this […]

A practical guide to spatial data management for inspection workflows on AWS Introduction Across industries, inspection teams are under increasing pressure to document asset conditions accurately, support compliance requirements, and maintain records that remain meaningful months or even years after data is captured. In practice, many inspection programs generate large volumes of imagery and observations […]

Introduction Answering technical questions that span multiple specialties is rarely just about finding the right answer. One of the hardest parts is often coordinating the right people to provide it. What if AI could augment this coordination—not by replacing expert teams, but by accelerating their initial research and synthesis? When complex technical questions span multiple […]

The open-source Visual Asset Management System (VAMS) now supports GPU-accelerated reinforcement learning (RL) for robotic assets through integration with NVIDIA Isaac Lab. This pipeline enables teams to train and evaluate RL policies directly from their asset management workflow, leveraging AWS Batch for scalable GPU compute. Isaac Lab for Physical AI and Robotics Development Figure 1: […]

Introduction The world is moving towards an Autonomous Economy which represents a transformative economic model where AI, edge computing, robotics, spatial intelligence, and simulation technologies work together to enable systems to operate autonomously with minimal human intervention. Physical AI represents the convergence of these technologies enabling computers to sense, understand, predict, and act with the […]

Note: This blog was updated on May 6, 2026 We have reached a milestone in technical evolution: the ability to use advanced AI models to influence not only the digital world but also the physical one. We are moving from AI that generates text to AI that moves atoms — augmenting our daily lives by […]

AWS re:Invent 2025 is just around the corner, and Spatial Computing & Physical AI specialists will be on hand at the event to share exciting technical presentations, workshops, chalk talks and more. Please join us to learn how AWS infrastructure and services enable autonomous systems to perceive, understand, and act in the real world. Key […]

The Challenge of Nutrient Management in Agriculture For decades, fertilizers have been essential to producing healthy crops and maintaining yield. Yet in many orchards today, especially those growing pistachios, grapes, and almonds across California, the benefits of extra fertilizer are beginning to level off. Growers often apply more nutrients than the plants actually need because […]