Runway 世界模型战略：从视频到机器人到操作系统的四章计划

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Hi friends 👋,

Happy Tuesday!

A couple of weeks ago, I mentioned that I was partnering with Runway this quarter as our presenting sponsor to bring some of my writing to life in the form of video. It took us a while to land on the right partner to form a deeper relationship with — it has to be a company I want to talk about a bunch — but when Runway reached out, it was a clear perfect fit. For one thing, I’ve had a lot of fun playing around with their video models. But for two others: 1. I’m fascinated by World Models (and quoted Runway co-CEO Anastasis Germanidis in the essay Pim DeWitte and I wrote) and 2. Runway has been on a tear with new product releases.

I wanted to understand how, so to kick off the partnership, I asked to write an essay with me explaining how video, interfaces, operating systems, and robotics all fit together, why video was the right starting point for World Models, where the world is heading if Runway’s bets are right, and whether or not, as someone who simulates worlds, he believes we’re living in a simulation.

Let’s get to it.

Runway: Learning From Watching the World

A Co-Written Essay with Runway Co-CEO Anastasis Germanidis

Cover image generated by Runway

From time to time, a certain company catches fire. You can tell when it’s happening by the pace and breadth of their product releases. One day, a new capability. Cool. The next day, another. Woah. Next day, another still.

Runway, the world model company best known for releasing the first commercial video generation model, is on such a run.

Over the past six weeks, it has shipped a real-time interface model, a new interactive world model, an open-weight robotics model, an AI agent for performance marketers, a research preview of an operating system, and it bought a robotics lab in Paris along the way. Meanwhile, the business is growing faster than at any point in its history, adding more than $100 million in annual recurring revenue in the last quarter alone. From the outside, it looks like a company that suddenly figured something out.

From the inside, the view is much more interesting. Runway has been pursuing a particular set of bets for eight years, and that near-decade of research and iterative deployment is now yielding a seemingly disparate but actually related set of new models and products.

On September 1st, Runway introduced Solaris, the “first Interface World Model,” which allows users to generate interfaces in real-time, through prompts or actions on screen, like this one where a guy takes a selfie and tries on glasses and tweaks his hair and smile with the drag of a mouse.

On September 8th, Runway announced it had acquired Kinetix, a Paris-based research lab, which specializes in… robotics? From the video company?

Then at their September 30th AI Summit, the team shared Praxis-1, “an open-weight World Action Model that turns our video pre-training expertise into real world control for robots.”

The thesis is that while robotics data is limited, video data is practically infinite. So Runway pre-trains on video data and then uses that as a policy model for robotics developers who can train it on their specific embodiments. Standard Bots, whose co-founder Evan Beard and I co-wrote an essay on robotics, is working with Runway to deploy Praxis-1 on its arms.

And then the very next day, on October 1st, Runway previewed Project Continuum, “a new operating system research application built around real-time video interfaces.”

A video model. An interface model. A robotics model. An operating system. Are you getting it? These are not separate pretrains. They’re different applications, built around the same General World Model backbone, with different post-training on top.

Made with Runway

All of them are examples of what you can do when you can simulate any pixel.

An operating system ends up as pixels on a screen, like video and interfaces do, and like the world does through a robot’s eyes. If you can simulate every pixel at high enough fidelity and speed, then you can make almost anything that shows up to the world as pixels. This is the future Runway is building towards.

Runway is making a few different bets, on a research direction, the Bitter Lesson, and a business strategy. It is betting that world models can learn, like humans do, from third-person observation. It is betting that letting models watch a ton of video will lead to models that understand how the world works better than they could by reading about how the world works or from any other human-mediated data source. And it is betting that it can build a massive business in content creation in order to both help fund the large investment into better and better models, and to become the rare company that is both a frontier lab and a distribution layer.

Runway’s commercial success and product prolificness points to a surprisingly wide set of applications for World Models; surprising, that is, unless you read the essay Pim DeWitte and I co-wrote explaining why World Models have the potential to eat everything. In it, we wrote:

World models — these systems that learn from watching the world and the actions taken in it — are a fundamentally new kind of foundation model. They can compute what was previously uncomputable.

There are a number of different types of models whose makers call them World Models, although many don’t fit our definition; they don’t predict the next state based on intervention. We categorized Fei-Fei Li’s World Labs, which AMD recently agreed to acquire for $8.2 billion, as building “3D Reconstruction and Generation Models.” Runway, we wrote:

Is blurring the lines between video generation and world generation, as mentioned in the Video Model section. During its Research Demo Day 2025, Runway co-founder and CTO Anastasis Germanidis explained the company’s evolution that started from “generative AI models [as] viable tools for creative expression”. They then evolved towards World Models (while still making incredible progress in video models.)

“To build a World Model,” Germanidis explained, “We first needed to build a really great video model. We believe that’s the right path to building World Models, that teaching models to predict pixels directly is the best way to achieve general purpose simulation.”

Runway first mentioned its World Model ambitions in a December 2023 blog post by Germanidis, who is now co-CEO, titled “Introducing General World Models.” This has been the plan for quite some time: teach the models to make videos from watching videos, and then teach them how to bring the actions in video to life.

Anastasis describes it as a plan in four chapters:

Chapter 1: Media and Entertainment

Chapter 2: Broader Content Needs and Full Video

Chapter 3: Robotics (We Are Here)

Chapter 4: Science

The plan is coming together, as evidenced by the recent string of releases, and I have become a World Models convert who believes they have the potential to do a lot of things in the real world that LLMs can’t, so Anastasis and I decided to co-write an essay on the company’s bet that watching a lot of videos can teach models to do almost anything.

Learning from Watching

One of the things you realize when you have kids is that babies are learning machines. When they’re really young, they just keep changing, picking up new skills, like little Neos.