Over $2 billion flowed into industrial robotics in the first half of 2026 alone — yet 90% of U.S. factories still run without a single robot. The capital is not the constraint.
Three software-native defense startups are now valued higher than most traditional prime subsidiaries — and they're winning contracts the primes weren't positioned to compete for.
The lessons from large language models don't transfer cleanly to embodied systems. Action spaces, physical grounding, and the sim-to-real gap make robot foundation models a fundamentally harder problem — and a more interesting one.
How edge inference hardware is being redesigned from the ground up for the latency-sensitive, power-constrained demands of robotics and industrial control — and why the programming model matters as much as the chip.
ROS 2, VxWorks, Apex.OS — why the choice of RTOS and middleware defines a robot's capabilities more than most people realize, and who's winning the infrastructure layer.
Force control, backdrivability, and thermal limits are quietly the hardest problems in robotics. A deep dive into actuator technology — and who's actually solving it.
Physical AI is not just robotics with better software. It's a complete reimagining of how machines interact with the physical world — from perception and manipulation to long-horizon reasoning. Here's how I map the opportunity across the stack.
After a decade of deep learning breakthroughs, robotic vision in unstructured environments still fails in predictable ways. Here's what's actually working — and what isn't.
Industrial hardware companies are drowning in embedded systems debt. The software running most factory robots is invisible, unglamorous, and spectacularly bad by modern standards. It's also one of the best investment opportunities in the physical economy.
The drop-in robot pitch is irresistible. A machine that looks like a person can work anywhere a person can. The economics of that pitch, in most factories today, are mostly wrong.
NVIDIA dominates AI training. But edge inference for robots — low-latency, low-power, industrial-grade — is a different problem entirely. A new wave of custom silicon companies is racing to own it.
The biggest bottleneck to deploying more industrial robots isn't the robot — it's the training data. Synthetic data from simulation is solving the cold-start problem, but the sim-to-real gap is still real.
