“The washing machine has changed the world more than the internet has.” — Ha-Joon Chang, 23 Things They Don’t Tell You About Capitalism Imagine what Physical AI could do when it automates everything. Physical AI > Digital AI.

Even more unexpectedly, Newton RF also performed strongly on non-RF tasks like vibration, audio, EEG, and seismic data. That means we should be able to expand Newton into the one model that understands any physical phenomenon, reads any sensor, and works for any use case. One world model that encodes the entire physical world. Full research: archetypeai.io/blog/newton-r…

Newton now understands radio frequency (RF) data! We just released results comparing a new Newton RF model against specialized RF models. Newton RF was trained on a large volume of RF data that looks nothing like other physical measurements, and we improved the model architecture to capture the spatial signal characteristics inherent to radio frequency. The results: Newton RF beat all five specialized RF models in 18 of 20 radio tasks, including localization, channel modeling, and blind demodulation. This is remarkable. In RF, models are highly specialized, each carefully designed for a single task: one model to decode, one to localize, one to identify the transmitter, and so on. Jonah Casebeer and @_jaimelien_ have proved that our Newton world model can rule them all!

Say “AI in the physical world,” and everyone pictures a robot. The robot is the least interesting part of the story. The opportunity goes far beyond robots: models need to learn from real sensor data, adapt as physical systems change, and run on the edge and offline. Thanks to @TechCrunch for having me and giving me the stage to discuss what it will take to bring AI into the physical world with @ethanjb and @IanRountree.

I'll be speaking at the TechCrunch Disrupt Breakout Stage in 15 minutes alongside @ethanjb and @IanRountree. See you at 11:30 a.m.

Roughly 85% of the global economy is tied to the physical world. Manufacturing, construction, and logistics are where AI can have a real impact. I joined Inside the Silicon Mind to talk about Physical AI and how one model can generalize across an entire fleet of machines without a custom model for every use case. Thanks for having me. Full episode: youtube.com/watch?v=ZpOOpAOp…

Physical AI systems are already pretty good at describing the world. The next logical step is to act on it: perceive, decide, act, verify. Next week, I’ll be on a panel with @ethanjb, and @IanRountree at TechCrunch Disrupt. Our panel is called “Physical AI isn’t a Model Problem, it’s an Execution Problem.” Join us to understand what separates intelligence that can generalize to the variability of the physical world from intelligence that doesn’t.

Proud of our team! @FastCompany named Archetype’s world model, Newton, one of its Next Big Things in Tech 2026 for foundational AI. Our ambition: encode the entire physical world in one AI model, extending our understanding beyond the limits of human perception. Honored to see @PhysicalAI alongside @cerebras @liquidai @GoodfireAI, pushing the boundaries of AI together. Onward!

Video is overrated. Nature’s vital signs—sound, vibration, electromagnetic signals, motion—reveal faults, strengths, and what’s happening inside an oil well, furnace, or nuclear reactor. No camera. Like a doctor saying “cut carbs, exercise more” just by reading your blood sugar and weight alone, without ever seeing you.

“Companies that are still in denial about Physical AI may not be around to see it play out.” 100% agree with David Brousell: AI moves gradually, then suddenly, as Hemingway put it. Thanks to Shahid Ahmed and @nttdata_inc for hosting the Physical AI Summit.

We showcased the Newton World Model demo live at @nttdata_inc's Physical AI Summit, running on real equipment and fully on the edge. We demoed two agents based on the same model. Newton discovers an industrial machine's operating states and anomalies from raw sensor data with no labels or prior training. The second agent helps operators catch missed assembly steps by observing operations from video. No retraining is required, just a list of tasks in text form. Supporting machines and people: both halves of Physical AI.

The root cause of AI anxiety: taking the red pill and the blue pill at the same time.