Over the last few weeks, we have seen some great improvements in the AI space around AI-generated video content. Most notably there is a pizza ad & a beer commercial that are worth a look. It is still early days for these videos but soon we will be able to give a prompt like “Make a 30-second pizza commercial for Brand Name Pizza” and we will have a compelling commercial.
We have already seen massive improvements in the realism of images thanks to AI like MidJourny & hopefully, soon DALL-E will also catch up so video is the natural next step in the progression. At present, AI-generated video content is primarily used to fill gaps in missing frames in videos. This is done by using machine learning algorithms that can analyze existing footage and generate new frames that are similar in style and quality. While this technology has been successful in improving the visual quality of videos, it still falls short of producing fully realistic video content.
However, recent developments suggest that we are getting closer to achieving this goal. Researchers and developers are now working on developing algorithms that can create full video content from scratch. These algorithms use a technique known as generative adversarial networks (GANs) to create video content that is not just realistic but also visually stunning.
The process of creating AI-generated video content using GANs involves two main steps. The first step involves creating a generator network that can produce video content. This is done by feeding the network with a large dataset of existing video content, which the network then uses to create new content.
The second step involves creating a discriminator network that can distinguish between real and generated video content. This network is trained to recognize differences in visual quality, style, and other factors that differentiate real video content from generated content.
As the generator and discriminator networks are trained, they continue to improve their ability to create and recognize realistic video content. This process continues until the generated content is indistinguishable from real content, resulting in a video that is visually stunning and fully realistic.
While we are still in the early stages of this technology, the potential applications of AI-generated video content are vast. In the film and entertainment industry, for example, AI-generated content could be used to create realistic special effects, reducing the cost and time required for traditional animation.
In the marketing and advertising industry, AI-generated video content could be used to create personalized advertisements that are tailored to individual users’ preferences and interests. This would allow marketers to create more effective and engaging ads that are more likely to convert viewers into customers.
We are about to see a world of possibilities open up, soon the companies that create multimillion-dollar ad campaigns will be competing against 15-year-old kids sitting in their bedrooms directing cinematic masterpieces in a single afternoon.
