text-to-video

AI Text-To-Video Generators: What Are They, and How Will They Boost Marketing Sales?

Image-generating algorithms that use existing images to create new pictures based on written text are the buzz in social media and AI development. The most popular and the most sophisticated text-to-image generators are Imagen, Midjourney and DALL-E 2

Even though companies, researchers and social media have been fascinated by AI text-to-image generators recently, some companies are already moving on to the next frontier: AI text-to-video generators. Text-to-video technology is in its very early stages of development, but it will be the future of marketing. 

This article will introduce text-to-video AI generators: how this technology work, which companies are leading on this new technology, and why every marketer should wait for AI text-to-video generators. 

Text-To-Video Generators: How Do They Work?

Text-to-video generators, as well as their text-to-image predecessors, use natural language processing and machine learning algorithms. Text-to-video generators can vary according to the company. Some companies use autoregressive transformers in natural language modeling. The autoregressive transformer is a decoder that tries to guess the next move or pattern of the image. Other text-to-video generators, like Google’s Imagen video, learn from image and video datasets with already given descriptions. The article will discuss the main text-to-video generators and their technical differences in the chapter below. 

Text-to-video conversion is more demanding and complicated than text-to-image generators. AI generator has to work harder to predict how well the image shift in time and has to produce numerous images in sequence to capture motion. Another issue is the lack of large datasets with high-quality videos and the issue of modeling data. 

Also, video frames start to deviate from the prompt if the prompt does not contain sufficient information for the subsequent changes. For example, the autoregressive model may be good at creating videos with regular and random patterns because they don’t require the model to figure out the action. But the model finds it harder to depict a specific action, for example, a lion drinking water. This is why the first text-to-video generators focus on simple video generation, such as moving digits or specifications.

Companies Working On AI Video Generators

Meta (former Facebook) is a leading company in text-to-video generators. Meta started to work on this project last year and recently launched a series of short video clips generated by the algorithm called “Make-A-Video”. Meta is using an autoregressive transformer model without video datasets. 

The generator works like a text-to-image system. The user has to type a scene, and the AI will generate a short clip that matches the description. This system learns how the world moves from video footage with no associated text and what it looks like from paired text-image data. 

Meta’s text-to-video generator can provide videos without learning visual and multimodal representations, and it does not need paired text-video data to produce the video. The videos are diverse and colorful in aesthetics and imagination, differing from the video or image datasets used to create them.

However, the video quality is artificial. The videos feature blurred objects and landscapes; some subjects do not have clear lines. Some of the generated video clips precisely depict the idea of the prompt and have high-quality motion. In contrast, others are less precise and a bit creepy. For example, the video clip with a cat watching TV mixes the lines of the cat, presents the cat in an artificial anthropomorphic pose, and gives odd anthropomorphic features (human hand) for the cat. 

Meta will release a demo available to the public, but the date of its release and access possibilities are not specified. Users might be able to use their images to produce the video material, too.

text-to-video
Source: https://makeavideo.studio

Cogvideo is another project aiming to generate AI text-to-video. Just like Meta’s AI text-to-video generator, it is an autoregressive transformer that focuses on applying DALL-E 2-generated images to a video format that is not yet available to the public. 

CogVideo is of 9.4 billion parameters and is trained on 5.4 million text-video pairs. Cogvideo is trained in multi-frame-rate hierarchical training, which prepends a piece of text describing the frame rate. That helps to align text and video in a better way.

Applying it to practice has many downsides: training from scratch is unaffordable in Cogvideo’s case because the computation costs are too high. Also, there is a weak relevance of text-video datasets making the model domain-specific and small databases.

text-to-video
Source: https://www.youtube.com/watch?v=whd4JCUZKJA

Imagen Video. Google recently announced the launch of a new AI text-to-image project Imagen Video, based on a previously launched Imagen text-to-image system that uses moving pictures, resulting in videos that remain consistent throughout each frame. Imagen Video was trained on 14 million videos and 60 million still images, along with another 400 million images in the LAION-400M open dataset.

The system can identify videos and still images defined by a given natural language description. AI replicates images in the form of a video when given a text prompt. The model can generate video in various animation and artistic styles. The system can work with 3D objects and create videos with objects rotating while preserving the structure. Imagen Video will create 1280×768 resolution videos at 24 frames per second from a written prompt.

At the moment, the model struggles with rendering complex movements and motion. Imagen Video will be able to produce high-quality, longer, and unique video content. 

text-to-video
Source: https://imagen.research.google/video/

Marketing and AI Text-To-Video Generators: Why Wait for a Text-To-Video Generator Boom?

Video is a great tool to expand your content strategy and keep your customers engaged. It significantly increases brand awareness, and traffic and drives sales. Videos help to stay visible for longer on social feeds, stand out more, provide a more personable way to engage with the audience, rank higher in search, and are more popular on social media platforms. 

Social media giants like Facebook, Instagram, Twitter and LinkedIn prioritise videos on their platforms to meet the expansive video demand. Now, these sites introduce video-friendly possibilities like live broadcasting and making a short video story. 

This is why videos are so important in marketing. Video is the future of marketing because the newest research shows that people love videos. For example, HubSpot found that 78% of people watch online videos every week, 54% watch videos every day, and Google’s research shows that 6 out of 10 people would rather watch online videos than television.

Text-to-video systems might be developing at a slower pace due to the near-limitless complexity of the subject matter. However, there are many reasons to develop these systems. Firstly, the prize of seamless video generation will motivate many institutions and companies to invest heavily in the project.

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1. Text-To-Image Videos Can Illustrate Your Product or Service on Social Media

By using AI text-to-video generators you can help the customers learn more about the product. Customers are more prone to buy the product when they understand what it does and how it will help them. The research shows that 72% of customers learn about a product or service via video content, and 50% of internet users look for videos related to a product or service before visiting a store [11].

Customers want to know as much as possible about the product, and AI text-to-video generators can clearly explain how your product works, what it can be used for, and how it looks and fulfills its function. The videos can be educational to the audience and show how the product fulfills their needs. 

Using text-to-video generators for social media sites to produce high-quality content without skills and financial investments

Short AI-generated videos can be used in various social media to catch the attention of possible buyers. For example, you can create engaging short video content for Youtube stories or a short video for Tik Tok or Instagram to attract attention. For example, in Tik Tok, the video quality has to be high, but it is not easy to produce such quality. You may need a professional camera operator, a film in high definition, ensure good sound quality, and perhaps even travel for shootings. All these things can be expensive or not possible for a young business. Text-to-video generators can help to create high-quality content fast without spending a lot of money on equipment and studying video making. 

text-to-video
Source: https://80.lv/articles/cogvideo-new-method-for-generating-gifs-from-text-input

2. Text-To-Video Generators Can Help You to Rank Higher

Google rankings prefer unique and refreshing videos. Google rankings are important. After all, they can show your site higher or lower in the search because more people will see your page in the search results. That will result in a better brand image and higher sales. Also, videos help to increase the metrics of users spending time on your page and the number of backlinks referring to your site. Videos boost both of these metrics. Studies show that people spend over twice as long on a page with video than without, and the higher the quality of your content, the more likely you are to get backlinks.

Text-to-video generators will allow you not only to brand your product or service with original content but will also help you to stand out in Google rankings and boost your image, too. However, Google may remain a bigger fan of human-generated content. Google’s understanding of the AI generator’s role in SEO is still a bit murky and undefined. 

AI GPT-3 model-generated content is considered spam by Google and is against Google’s webmaster guidelines because it falls into the category of automatically generated content. But Google is not able to detect AI-generated content automatically and still needs human reviewers. The definition of AI-generated content may shift from automatically generated content status to a manual tool for humans because Google does not take into account how people use AI tools.

3. And Most Importantly, Originality

In today’s over-stimulated world, one has to create something unique and creative to attract attention. There are a lot of image stock sites as well as video templates that do not interest the viewer anymore. Text-to-video generators can unleash the fantasy and create engaging and capturing surrealistic videos illustrating the product or service to sell. Your brand can create a unique story thanks to text-to-image generators that will be 100% original.

Source: https://imagen.research.google

Conclusion

Text-to-video progress may be slower than text-to-image development, but it will be the future of marketing. Text-to-video generators will boost website or blog traffic, increase engagement, and produce unique and original image content that will win customers with creativity.

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