Below is the table of contents for this article, it is recommended to read it with key points in mind.
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01 Introduction to Runway
02 Features of Runway
03 Advantages of Runway
04 A Viral “Promotional Video”
05 More Than Just SaaS
06 Cloud-Based Software
07 Conclusion
01.Introduction to Runway
Runway is a platform that claims to be the next generation AI-supported video creative tool, supporting AI-assisted editing and generation of images, audio, and video, and it is also an AI training platform. Founded by three Chileans: Cristóbal Valenzuela, Alejandro Matamala, and Anastasis Germanidis at the end of 2018, it was initially developed as a thesis project at New York University (NYU), where they met and obtained their graduate degrees.
Runway received $2 million in seed funding from Lux Capital in 2018, and completed three rounds of funding (A, B, C) from 2020 to 2022, with the C round led by Felicis, raising $50 million and achieving a valuation of $500 million.
The main user groups of Runway include filmmakers, designers, VFX and CGI professionals, artists, coders, musicians, students, and educators. They received strong support from academia in their early development and established close alliances with U.S. universities such as NYU, MIT, and UCLA. In Chile, Runway is already being used at Adolfo Ibáñez University, Las Américas University, and the Pontifical University of Catalonia. Computer, design, and art professionals use the RunwayML platform for AI training and synthesis in images, videos, audio, etc., and utilize the relevant AI tools provided by Runway for research and design.
Video Editing
Video editing is Runway’s flagship feature, with basic operations similar to Capcut, but incorporating AI tools called Magic Tools. The main AI-assisted features include: Green Screen, which allows you to cut out selected subjects as video themes using green screen technology, automatically filling in the contours that fit the theme through point selection; Inpainting, a video restoration function similar to the Photoshop function for images, where you manually select the object range to remove the subject within the selected area and fill it in with the surrounding background using AI calculations; Motion Tracking, which allows you to select a subject in a video, so when you add other effects (like titles), they can follow the movement of this subject.
Image
The main feature related to images is text to image generation, which has decent clarity and resolution, but the degree of realism needs improvement. The examples in the images are a husky I generated (prompt: a husky dog) and an Alaskan malamute (prompt: an alaskan malamute). The not-so-smart sled dogs look even sillier, with a “Frankenstein” vibe.
For audio processing, it includes four functions: Clean Audio (noise reduction), Remove Silence, Generate Transcript, and Generate Subtitles, which seem to be similar to the functionalities of Krisp and Descript.
03.Advantages of Runway
It seems that Runway’s main goal is to capture a portion of the traditional post-production software market and carve out a niche in the creative tools space. Runway’s biggest asset is its relatively advanced AI capabilities and the derived Magic Tools. In video post-production, the most time-consuming tasks are likely Green Screen (chroma keying) and Inpainting (image restoration), and with the help of AI tools, Runway can save a significant amount of time while achieving comparable results.
On Runway’s official podcast, there are two examples, one comparing the time taken for subject selection using RunwayAI tools and Adobe AE tools (https://runwayml.com/blog/future-of-ai-and-video/). Runway, through simple point selection and remote computer processing, only took 5 seconds, while the Rotobrush in AE required multiple manual adjustments and corrections, taking about 20 seconds.
The other example (https://runwayml.com/blog/introducing-sequel/) compares Runway with traditional post-production tools. They first filmed a video of a young man doing a backflip in an office (about a few seconds) and needed to cut the person out from the background and add a fire effect. A total of four editors were compared: two used traditional post-production software (one with a drawing tablet, one using traditional software), and two used AI software (Runway and Adobe). The two using AI software completed the production and export in 6 minutes, with Runway achieving better results, while the other two using traditional tools only completed a few frames of keying, falling far behind in progress.
04.A Viral Promotional Video
Runway made a particularly cool promotional video, a short 1-minute piece that appears to operate entirely through text commands – input commands -> confirm -> receive results, seemingly aligning with the vision in the promotional video: “Edit video using text, Generate video using text, Make video using text.” However, in reality, the promotional video was also edited together, and actual usage still requires a lot of mouse operations, with text accounting for less than 10% of the process.
It is understandable; after all, you can’t expect the packaging and promotional video of a product like Master Kong’s beef noodle to be perfectly aligned with the final product.
There are also completely AI-generated video works, the results are mostly closely related to abstract art, or to put it bluntly, they are not as good as simple drawings made by kindergarten children. In the field of AI-generated videos, there is still a long way to go before practical use.
Another highlight of Runway is that as an AI platform, you can upload your own images for training. In the early stages, there was a time when you could upload your own models and combine them, meaning the output of one model could serve as the input for another, with orchestration completed through visual drag-and-drop. I thought this feature is like the Zapier of the AI world.
Runway essentially possesses both SaaS and PaaS functionalities, and with the added AI buff, it’s a full-spectrum offering, no wonder it has been able to secure funding quite smoothly.
All AI-related computations for Runway are processed remotely in the cloud, with users only needing a browser window. Audio and video transmission can consume a significant amount of network bandwidth, and Runway has optimized this issue with HLS (HTTP Live Streaming) (https://runwayml.com/blog/distributing-work-adventures-queuing-and-autoscaling/). Currently, the number of users is still relatively low, but once user growth explodes, the network and server costs will also be a considerable investment. If we factor in the servers used for AI, the costs could be even higher.
Currently, Runway’s AI tools total 30, covering four major categories: audio, image, video, and text, basically encompassing all the AIGC functionalities you can think of in the market. For creative professionals, it’s a good tool for improving efficiency; for researchers, it can also serve as an AI platform.
Beyond the exaggerated promotions of the promotional video, Runway is essentially a tool for enhancing efficiency in general audio and video editing with AI, and its most successful feature is helping video creators reduce repetitive tasks.
In the comments section of Runway’s promotional video on YouTube, a user mentioned that an urban promotional image at 49 seconds was generated by him using stable diffusion, which feels strange as it creates images but does not own them.
General generative AI is still far from widespread real-world application, while AI that replaces repetitive tasks or reconstructs copies is gradually maturing.
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