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12 resources
The site of Skild AI, a robotics company building a general-purpose "robot brain" — foundation models meant to control many kinds of robots.
The site of Waymo, the Alphabet-owned autonomous-driving company that operates a driverless ride-hailing service in several US cities.
A Stanford research project page describing HomeBody, which gives vision-language models a humanoid robot body through persistent spatial memory and reusable skills, without training for each new environment. Results are the authors' own and include demo videos.
Microsoft Research blog post on running the heavy AI thinking for robots on remote computers instead of on the robot itself, and what that means for speed, cost and reliability in real-world robotics.
Why I recommend it: Free to read. Written by Microsoft researchers, so it presents their own approach favorably — Microsoft also sells the cloud computing this kind of setup relies on.
Resources from Princeton's robotics initiative, including research groups, facilities and learning links.
Why I recommend it: A starting point for exploring academic robotics; the page blocked automatic checks, so confirm links load for you.
The University of Pennsylvania's robotics and AI lab, covering perception, autonomous robots and machine learning.
Why I recommend it: Technical, but the project pages give a clear picture of real robotics work beyond the hype.
Research news from the University of Oxford's Department of Engineering Science: robotics, energy, biomedical engineering, AI and more.
Why I recommend it: A university news page, so it highlights its own wins. A handy way to spot new research before it hits the headlines.
Free daily-ish newsletter covering robotics developments — humanoid launches, self-driving expansion, home robots — written for a general technical audience by the Rundown team, with a stated readership of 300,000+.
Why I recommend it: Free and quick to skim if you want to know what robots are actually shipping rather than what is promised. Two honest limits: it summarises company announcements far more often than independent testing, so a capability claim in it is usually the manufacturer's own; and it publishes no public story feed, so it cannot be wired into the headlines here — you read it by subscribing.
The manufacturer's own pages for the humanoid and four-legged robots you keep seeing in viral videos — H2, G1, R1, A2, B2, Go2 and the L2 lidar unit. Each model page lists the specifications, dimensions, sensors and intended uses, and the news section posts the demonstration videos. This is the clearest free way to see what commercially available 'physical AI' hardware actually is, rather than what a clip implies.
Why I recommend it: Free to browse, and useful as a reality check when someone tells you robots are about to take every job — read the specifications, the battery life and the intended use. Two flags: this is a company selling its own products, so the videos are marketing and not independent testing, and the robots are expensive hardware, not something you can try. The site itself warns users not to modify the robots or use them in dangerous ways.
A free self-paced curriculum for the Forward Deployed Engineer role — the person who sits with a customer and turns an AI model into a system that actually runs in production. 11 modules, 150+ topic articles, 700+ open-book questions and 15 daily drill questions, covering systems thinking, problem decomposition, LLM/RAG/agent architecture, data and event systems, physical AI and robotics, plus client discovery, integration, deployment and stakeholder management. It also publishes a map of 15 layers of the modern AI engineering stack drawn from real FDE and AI-engineer job specs, with links out to where to learn each one.
Why I recommend it: The whole curriculum opens without an account or a card — I checked — and an account only saves your progress. There is no pricing page anywhere on it, so nothing is being held back behind a paywall today. Worth knowing why this matters: 'Forward Deployed Engineer' is a job title that is actually being hired for right now, and it pays like engineering while rewarding the consulting side most engineers avoid. Two flags. It is one person's independent site, not an accredited course or a certificate anyone will recognize — the value is the material, not a credential. And it makes a strong claim, that foundation models are becoming a commodity and the money lives in the last mile; that is an argument, not a measured finding, so read it as a well-argued position.
Berkeley faculty page for Anca Dragan, robotics and human-AI interaction researcher who also leads AI safety and alignment work at Google DeepMind.
From the site: Associate Professor, Division of Computer Science (EECS) — Anca Dragan is an Associate Professor in the EECS Department at UC Berkeley. Her goal is to enable robots to work with, around, and in support of people. She runs the InterACT Lab, where they focus on algorithms for human-robot interaction -- algorithms that m…
Why I recommend it: One of the few people working on alignment from the robotics side, where the system has to act in the real world. Her publication list is the useful part.
Open-access academic journal publishing peer-reviewed research on robotics, automation, and their economic and social consequences.
Why I recommend it: Free peer-reviewed research on automation. Denser than a blog post, but the citations are gold if you are writing or speaking on this.
