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Sharing Nils Pihl's SuperAI 2025 keynote here because it gives a really good picture of where spatial computing fits into the bigger AI shift.

Nils, the CEO of Auki, talks about what happens when AI starts moving beyond screens and into the physical world. Robots, cars, phones and AR glasses all need some way to understand the spaces around them, but that understanding becomes much more useful when devices can build and share a common view of the environment rather than each one working in isolation.

What makes the idea more interesting is the privacy problem that comes with it. If machines need to constantly understand the world around them

One thing I think gets missed when people talk about physical AI:

It's not just about building better robots.

A robot still needs to understand where it is, what's around it, and what's happening in that environment.

That's why the infrastructure behind physical AI is so interesting.

Better physical-world understanding could support synthetic training data, more accurate video understanding, and robotics models that can interact with real environments.

But if the infrastructure behind that intelligence becomes heavily centralized, we also end up with questions around [privacy, owners

Auki’s latest community update gives a clearer picture of what its spatial infrastructure could look like when robots start joining environments that already have a digital understanding of them.

The BracketBot demo is the part that caught my attention.

A remodeled lab was mapped using phones, and the robot was then able to use that existing map to localize, navigate, and build out denser spatial data with its own sensors.

That points to an interesting shift in how robots could be deployed: the next robot does not necessarily need to start with an empty map.

A few pieces from the update make that direction even more interesting:

- QR-bas

Auki's September 11 community update gave a clearer look at where it’s taking its work around physical AI.

The focus is moving beyond individual robot skills toward giving AI better context about the physical environments those robots operate in.

- Auki is rebuilding its open-source SDK around shared spatial context and networked scene graphs
- Cactus is an early version of this approach in retail
- The goal is to let different robots, sensors and devices work from the same understanding of a

Anthropic is previewing a shared spec for AI agents to operate physical equipment in research and manufacturing. That is a serious statement. It points machine control away from custom setups and toward a common interface.

Auki's response was the part I actually cared about. They agreed with the direction, then said operation alone is incomplete if machines still cannot be discovered and combined in the same environment.

That is why I take Auki seriously. They are not waiting for another lab announcement. They already have an SDK aimed at discovery, composability, and coordination across machines in real locations.

If AI is