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Runway
Runway builds generative video tools and world models, moving from creative software toward interactive simulation.
Runway is an AI research and creative technology company developing generative video, editing tools and interactive world models. Founded in 2018, it grew from tools that made machine learning usable by artists into a developer of its own image, video and multimodal models. Co-founder Anastasis Germanidis is co-CEO alongside Cristóbal Valenzuela; Kamil Sindi is CTO.[1][5][2]
From creative tools to video models
Runway’s early tools brought machine learning models into artists’ workflows. One of its most-used products was Green Screen, which helps isolate subjects in images and video—a task that visual-effects artists otherwise perform through painstaking rotoscoping. Germanidis says the tool was used in Everything Everywhere All at Once.[1]
In 2023, Gen-1 and Gen-2 brought video generation to Runway’s product suite. Gen-2 combined image and text inputs with motion generation; filmmakers’ feedback pushed the team toward controls for the camera and action, alongside improving image quality. Runway described this evolution in its Gen-2 research interview.[6][3][1]
Gen-3 Alpha, introduced in June 2024, was trained jointly on images and video using new multimodal training infrastructure. Its more detailed temporal captions supported controls such as transitions and keyframes. Runway framed the model as a step toward general world models in its technical announcement.[4]
WorldPrompt and real-time worlds
GWM Worlds 2 is a research preview for generating interactive video and audio. Its WorldPrompt format lets a user set parts of a scene and supply timed actions, including actions during generation. It is a prompting interface rather than a scripting language: users do not directly program every state of the world.[1]
To respond continuously, the model generates frames in sequence. Germanidis describes converting a model that generates an entire video at once into an autoregressive system and reducing the work required for each output. A central difficulty is error accumulation: generated frames feed the next prediction, so small mistakes can grow over time.[1]
Runway sees potential applications in games, creative production and robotics. Germanidis also draws a harder distinction between video that looks plausible and a world model that responds plausibly to different actions. In football footage, for instance, a model trained disproportionately on successful goals may depict goals more convincingly than misses.[1]
Financing
Runway announced a $50 million Series C in December 2022, led by Felicis, followed by a $141 million Series C extension in June 2023 with participation from Google, NVIDIA and Salesforce Ventures.[5][6]
Timeline
- release
Runway introduces Gen-3 Alpha
Gen-3 Alpha, introduced in June 2024, was trained jointly on images and video using new multimodal training infrastructure.[4]
Financing
Series C
Runway announced a $50 million Series C in December 2022, led by Felicis, followed by a $141 million Series C extension in June 2023 with participation from Google, NVIDIA and Salesforce Ventures.[5][6]
Series C extension
Runway announced a $50 million Series C in December 2022, led by Felicis, followed by a $141 million Series C extension in June 2023 with participation from Google, NVIDIA and Salesforce Ventures.[5][6]
From the Latent Space archive
Original posts and separately reviewed explanations.
Sources
- 1Runway’s WorldPrompt and the Engineering of Real-Time WorldsAccessed 2026-10-18
- 2New Leaders to Support Our Next Phase of GrowthAccessed 2026-10-18
- 3Scale, Speed and Stepping Stones: The path to Gen-2Accessed 2026-10-18
- 4Runway Gen-3 AlphaAccessed 2026-10-18
- 5Runway raises $50M Series CAccessed 2026-10-18
- 6Runway raises $141 millionAccessed 2026-10-18
Model source and teaching reviews passed. Human editorial review pending. This profile describes the sources as of 2026-10-18.