Setareh Lotfi
Marginalia

Annotated reading lists, kept in the margins.

III.

Embodied AI

A running list for anyone genuinely trying to understand what happens when intelligence learns to move.

Last updated Q2 2026

To get the lay of the land

  1. 1.
    Robotics Levels of Autonomy

    A useful framework for what "autonomy" actually means when people throw the word around. Saves you from nodding along when someone conflates teleoperation with full autonomy.

  2. 2.
    Thematic Primer: Humanoid Robots

    A solid sector overview if you want to understand the competitive landscape and where the major players sit relative to each other.

To understand what real progress looks like vs. a slide deck

  1. 3.
    State of Robot Learning, Dec 2025

    The best single overview of where the field actually stands. Worth bookmarking and revisiting — it ages well because it deals in evidence rather than projections.

  2. 4.
    The Physical AI Deployment Gap

    Captures the distance between what physical AI companies promise in demos and what they deliver in production. If you've ever watched a robotics demo reel and thought "that can't be the whole story" — this is the rest of the story.

  3. 5.
    1X World Model

    Shows what a real world model company looks like when there's actual technology behind the claims. A useful benchmark for evaluating anyone else who says they're building world models.

  4. 6.
    The Physical Intelligence Layer

    Physical Intelligence is one of the best-funded teams in this space. This piece shows how their general-purpose models are being deployed by real partners to solve real problems — a good reference for what "world models meeting enterprise" should actually look like.

For the bigger picture

  1. 7.
    All Roads Lead to Robotics

    A thoughtful, wide-angle essay on why robotics is where many of the most interesting threads in AI converge. Good weekend reading — the kind that reframes how you think about the whole field.

  2. 8.
    World Models: Computing the Uncomputable

    A thorough walk through the history, theory, and potential of world models — from what they are to why they matter for physical AI. If you only read one thing to understand why everyone keeps saying "world models," make it this.

  3. 9.
    Many Small Steps for Robots, One Giant Leap for Mankind

    Packy does what Packy does best — takes a sprawling, technical landscape and makes it genuinely fun to read. If the other pieces here are the syllabus, this is the one you actually enjoy doing the reading for.

This list is maintained as a living document. Pieces are added when they earn it, not on a schedule. If something here has gone stale or you think something essential is missing, I'd like to hear about it.