WorkshopIn personFree

Rooftop Happy Hour: Physical AI Data & Sim Infra w/Midcentury and AI Circle

NOV9
17:00

About this event

As physical AI moves from research labs into the real world, the infrastructure behind intelligent machines is becoming increasingly important.
From robotics and autonomous systems to embodied agents, progress depends on more than better models. It requires high-quality data, realistic simulation environments, scalable training infrastructure, and robust evaluation systems.
Join Midcentury and AI Circle for a rooftop happy hour during CoRL 2026, bringing together researchers, builders, and operators advancing the infrastructure behind physical AI.
We'll explore:
How physical AI data pipelines are built and scaled
The role of simulation environments and synthetic data in robotics training
The infrastructure required to train and evaluate embodied models
Bridging the gap between simulation and real-world deployment
How teams collect, curate, and evaluate real-world interaction data
What it takes to build production-grade physical AI systems
As the frontier shifts from models that understand the world to models that act within it, the quality of data, environments, and infrastructure will determine how quickly physical AI advances.
Because the next frontier isn't just artificial intelligence. It's intelligence that can operate in the physical world.
Refreshments and small bites will be provided.
Who This Is For
Researchers working on robotics, embodied intelligence, and reinforcement learning
Builders developing physical AI products and autonomous systems
Teams building simulation, synthetic data, and training infrastructure
Engineers and operators working on robotics data pipelines and evaluation
Investors and founders advancing the physical AI ecosystem
About the Hosts
Midcentury is an applied research lab building data and simulation infrastructure to scale physical AI. They recently emerged from stealth with their Series Seed and have licensed datasets to leading AI companies and frontier robotics labs. They’ve built the world’s largest egocentric dataset (2M+ hour

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