This article discusses the relationship between information, digital content and people from the perspective of content generation, as well as the logic of the development, presentation and future shape of content in areas such as media, gaming and social.
When we look at the whole of content production and consumption in a holistic way, there are 4 different stages of content generation.
- In stage 1, content is generated by large teams of professional creators (PGC) and most of these products are aimed at single-player experiences that don’t actually change when adding users to the product who are also engaged in content interactions. Examples include most of the news, streaming media, non-sandbox games and other content.
- UGC content such as communities, self-publishing, and sandbox games would fall into stage 2, while social media, social networks and communities would span both stages 1 and 2 in a broader sense.
- In stage 3, ABC technologies (AI, Big Data, Cloud) will help people generate digital content more efficiently, which will be naturally dynamic and therefore able to accommodate the dynamic experience of multiplayer interaction at the same time.
- Stage 4 will be the automatic generation of large amounts of rich content entirely by AI to support the demands of users when they consume content in the Metaverse.
In terms of the spectrum of real and virtual worlds, stage 123 is all about the digital real world, while stage 4 is entirely about the native virtual world.
On this basis, we further discuss the changes and impact of technology on several key content areas (media, gaming, community, social, etc.) and how content is being intelligently generated from the outside and the inside.
Technology will bring new social relationships for people in the virtual world and also new relationships of production. The current era of UGC and PGC will soon be over, and humans and AI will work together to create more dynamic, rich and personalised content.
I. Information, Digital Content and People
(1) Content = Information + Carrier
People are born into a relationship with the world.In this world, it is people and objects that can relate to each other. People communicate with each other, and in order to obtain information about each other, they create language; at the same time, in order to obtain information about objects, we create tools, and by using them, we obtain information about them and use them for various purposes, or even make them into tools ourselves.
The existence of information itself does not depend on the way, path or object through which it is transmitted; information itself is only related to the information carrier. In other words, when we acquire information from the real world, we are simply acquiring information that is already there in some reasonable way.
In the process of acquiring, transmitting and receiving information, we use various carriers in order to increase the efficiency of information acquisition. Words are virtual carriers, sounds are virtual carriers, tools are physical carriers and objects are physical carriers. Of course, virtual carriers must need physical carriers if they are to be more stable, continuous and effective.
When this process takes place, the shape of the information changes, because the carrier changes.
Strictly speaking, the written word is also a tool. At the same time, tools such as pens, paper, musical instruments and sheet music emerged as carriers of different messages to help them stay and spread among people in order for the language, and the ideas behind it, to be transmitted in a stable and effective way.
When information has a carrier, it becomes content.
The essence of content is information; people are information, objects are information, the language people use to communicate with each other is information, the videos people take are information, the things people buy every day are information. But strictly speaking, information becomes content when it has a carrier.
At the same time, words, images, music, people, objects and so on are all content. Before the advent of information technology, people could not communicate with people and the information they could produce, such as the words they said, the clothes they wore, etc., directly as content; if they wanted to communicate with someone, they had to visit them or wait for them to appear.
For content such as text and images, which were already in themselves as information carriers, it was possible to integrate content again through other tools, such as people using paper, engraving, etc. for multiple communications, etc.
(2) Form of Information
For the information itself, the one that is at the bottom is the logical type of information that enables one to recognise and understand other information in a reasonable way.
If we only had information and content such as language, words, images, shapes, temperatures, etc., we would indeed have direct access to them and each person would have their own way of understanding them to describe them. But if similar or identical logical parts do not exist, we cannot communicate with others about them.
Logical information is often not information that is at the level of the appearance of an object, but rather the way and manner in which people understand and perceive it.
The language we use every day is a natural language, which is an exhaustive language. Although the pronunciation of different linguistic units varies, there is a finite number of phonemes that form the basis of a language, usually only around 40. At the same time, because words are formed from a finite number of base phonemes, the vocabulary that makes up any natural language script is also finite. As a result, the number of corresponding sentences is also limited.
In mathematics, logic and computer science, on the other hand, a formal language is a language defined by means of precise mathematical or machine-processable formulae. In the theory of formal languages, it is a collection of certain finitely long strings on an alphabet, and a formal language can contain an infinite number of strings.
We already know that purely mathematical and logical languages cannot describe the system itself within the system, while information represented through logical languages cannot give a complete representation of the content of information in different contexts.
In addition to using logic within different systems, people also quickly understand and perceive other information through other means such as analogy and association.
In this process, text, image and sound information, which are at the surface level, are the most direct ways of accessing them. In addition to this, there are also forms of information such as smell and touch that help us to perceive and understand information and content.
The development of technology has made it possible to disseminate this superficial information in a more stable and effective way. From paper to telegrams to text and images on the internet screen, we are constantly digitising information about objects in the real world to become digital content.
At the same time, the person in the real physical world, whose information and content is uploaded to the web by way of data, becomes digital content.
For technical reasons, we can temporarily digitise only part of the information, such as basic information (name, age, place of birth, etc.), portrait information (photos, videos, etc.), preference information (types of videos viewed, tags, etc.), behavioural information (alignment in games), etc., thus approximating the image of the person in the virtual world.
(3) Relationship between Information and Digital Content
As we mentioned before, content is information that has a carrier. The coincidence is that in the real world, we also know people, objects and things through fragmented information.
Only in such scenarios as learning about knowledge, work, etc., we integrate this fragmented information to form systematic information in order to increase the efficiency of information reception.
The information on the web is all information with a carrier, so broadly speaking they are all content. Thus, the relationship that exists between people and information and content in the web becomes:
This is a simple model of different people taking content from the real world and converting it into content in the virtual world, it also represents the carrier of different people’s information on the web, which can be voice, text, pictures or videos.
At the same time, due to the fact that digital information can be edited and modified many times, people in turn rework the information in the virtual world into new content.
Of course, not all information can be modified; for example, some information involving authenticity, confidentiality and uniqueness cannot be modified, or requires permission.
We refer to the information that has been modified and edited as “digital content*” . This content is modified from digital content and people will interact with this content as well. This content is information that originates from the real world and is therefore classified as digitised real world.
In the real world, when people want to exchange information, there are several scenarios.
- One is where people will get together to discuss and express their opinions on a topic and will record it so that someone else can have a more complete picture of what they are discussing.
- In another case, one of the people has more insights and everyone wants to come and hear what he has to share, and then therefore gathers and keeps the contents on paper at the same time.
- Another scenario is that the person has some characteristic that everyone wants to access, but it is not available to everyone at the same time, so it will be disseminated by way of content.
Content is inherently time-sensitive; digital technology simply gives the optionality of timeliness. People can actively choose to set part of their content to exist for a long time, or set another part to be read and burned. This also opens up the possibility of documenting the forms in which content can be distributed.
(4) Form of Digital Content
From the point of view of content production, information from both the real world and the virtual world can be extracted and transmitted by people or machines.
Using a machine to extract information from the real world means setting rules for the machine to automatically follow in certain scenarios to recognise and record information such as text, images, music, etc., and to store and transmit it in the form of content in the virtual world.
For the human being, who can use a terminal to digitise information from the real world, there is in fact an implicit point: to carry out this process from his or her own perspective.
This comes back to people, who see the world in whatever way they can access information digitally.
According to an analysis by researchers at the Harvard Business School in the USA, the human brain receives external information every day through five senses in the following proportions: taste 1%, touch 1.5%, smell 3.5%, hearing 11% and vision 83%.
In terms of feasibility, both taste and smell require special molecules to be perceived, and touch requires a corresponding tool corresponding to real-time control to be perceived. The visual and auditory modalities, on the other hand, have the lowest requirements for communication and perception, requiring only a screen and a generator.
As a result, text input, photographic images, video recordings and audio samples have become the most dominant forms of digital content. Of course we would also like to see in the future ways of digitally distributing the senses of touch, smell and taste, thus increasing the form of content and allowing for a more immersive perception of the virtual world.
As for the content produced in the native virtual world, they have the same form but carry different sources of information.
(5) Relationship between Digital Content and People
Once we have clarified the form of digital content, we can then move on to discuss the relationship between people and digital content once it has emerged, in order to understand the emergence and evolution of the content industry.
In the earliest days, the lack of advanced tools and carriers and the different forms of organisation corresponding to the different stages of social development led to the production of information initially originating from only a few people, who then used non-digital carriers to disseminate the information, which would have taken a very long time and the information could not be received by a larger number of people in a fast, timely and consistent manner.
The tools used to expand and extend the transmission of information are medium, which are the various intermediaries that bring two parties into relationship, such as text, sound, graphics and images, animation and video; in the English context, media is called medium, which refers to the content used to communicate, or the material carrier of the message.
Media, on the other hand, are the carriers that carry the medium, such as newspapers, radio, television, films, games, websites, blogs, microblogs, WeChat, etc. Those based on analogue media are called traditional media, while those based on digital media are called digital media. Media is the plural of medium, which is understood as a collection of all media, not just mass media.
At the same time, medium also refers to the material of the media, such as tablet, paper, disk, CD-ROM, tape, semiconductor memory, bio-memory, etc., which can also be divided into analogue and digital mediums.
The form of the media, in fact, determines the way in which it is disseminated. Before the advent of information technology, the media were mostly physical objects of the printed type; the advent of computers and the Internet gave birth to electronic media. Due to the development and popularity of technology, this form of media was at first centralised, with those who had the advantage of information, taking it upon themselves to spread it through the internet and thus gather a corresponding audience and users.
As technological breakthroughs enabled more information to be converted into content in a more efficient way and then digitised, the volume of information in the online world grew in a single burst, the pace of which was reflected in the changes in supply and demand for information and content.
Initially, when websites emerged, the demand for quality content was not high (or rather, the demand for real-time interaction with high-quality images, videos, etc. was not yet present), so it was more efficient and profitable to consolidate and publish information in a centralised way than to publish one’s own information about a particular area on one’s homepage.
As media sites have seen a concentrated explosion, the supply of content has correspondingly increased dramatically. To enable people to find targeted information more quickly, search engines were created on top of portals and web content, which also greatly increased the efficiency of access to information.
This period is also known as the 1.0 era of content. The relationship between digital content and people is driven by the volume of the content and is therefore subject to many external factors, especially the overload of information which also weakens the relationship between digital content and people by making the content continuously less attractive to people.
We mentioned above that information about people themselves can be digitised, and as information in graphic form becomes increasingly saturated, people’s needs change from access to information to communication. This is consistent with the process that happens to people in the real world: having known the world, they want to communicate.
Thus, after the advent of portals and search engines, social networks emerged to connect people. People turn their information into digital content through various accounts on the web. This content contains not only basic information about the user, but also the content of the interactions that people have with the real world.
The internet has made it possible for people to interact with each other more quickly, and people are gradually moving their real-world social relationships into the digital world.
What needs to be made clear here is that what we want to access in real-world social interaction is the attributes of people themselves, and the information and content that they produce.
Social networks digitise part of the attributes of people and their content, allowing us to access this information in a quicker and more efficient way, while other parts of the attributes cannot be digitised.
At the same time, social networks, because of their social nature, connect different people based on layers of relationships around them. So social networks themselves are highly dependent on real-world connections.
The focus of social networks is not on pure content, nor on pure people, but on the content generated by the connections. The content has this characteristic, which allows people to convert interactions through digitalization into interactions in the real world.
Social media was born at the same time as social networks, and these two forms form two different lines of development in the 2.0 era of content.
The similarity lies in the shift in focus from the content itself to the people, specifically, the emphasis on content that is relevant to people. The difference is that the path of social networks is “people before content”, while the path of social media is “content before people”.
Since digital content is inherently media-like and the web brings people very close together, social media and social networks share some of each other’s attributes.
At the same time, the focus of social media is on media-style centralised content, rather than decentralised content built on human connections. Thus, social media is really about building media content from high to low by stratifying real-world people according to their influence, and continuously adding digital content through people.
Social networks, on the other hand, are about taking digital content from everyone in a more equal way. In the process, there will be people who stand out and take on the attributes of the media by being noticed by more people for the content they produce.
In this process, both social media, social networks and self-publishing start out by putting as many different areas and forms of content as possible into the same system of existence, so as to attract users better.
As the organisation formed by people and content expands, the quality of the content decreases. When the user’s tolerance for bad content outweighs the value he gets from it, he leaves and looks for other places to gather content.
For social media, the way to deal with this situation is actually a trade-off strategy, because it is concerned with the vitality of social media as a whole rather than the mere attractiveness of the content, so its strategy will tend to favour the content produced by the head users and the the tail users, which are both relatively extreme in terms of content quality.
The middle part of this user segment will then move in part to more vertical content aggregators that become communities.
Communities and social media are thus alike in that they are both content-oriented places at their core. Of course communities can also be made up of a very wide range of content from different fields, but the difference between communities and social media is that communities are marked by equality and do not influence the distribution of content because of the size of the user’s influence.
Users themselves make their own choices of content on different topics and from different people, and generate many-to-many web-like interactions based on content in an equal exchange relationship.
The difference is that with the addition of self-publishing to social media, centralised and decentralised communication will co-exist. However, in the early stages of development, centralised communication influence will occupy a more dominant position in social media, while community communication will be flatter.
Self-media was born out of social networks when more and more people took on the attributes of media.
In fact, by definition, self-media refers to mass communicators delivering information and content to an unspecified majority or a specific single person with the help of online means. Thus, users can become self-publishers anywhere, as long as they are given the tools to distribute their content.
So the question is, why is self-media preferentially born in social networks? Actually, this question is very easy to answer. An equal relationship between different users and content is more conducive to the emergence of self-publishing. If there is a pre-existing influential authoritative media, individual launches of content are naturally suppressed by the existing media and thus cannot be spread quickly and at scale.
While initially users will choose to use social media to post content in an attempt to use the existing body of users to help build an inner circle, there are three ways in general that have proven to aid the spread of self-publishing.
- In social media, based on existing relationship chains or other factors, self-publishers in social media are able to reach out to headline or authority media to grow their influence quickly.
- In communities, users become self-media within a community by contributing consistently to a particular area or topic.
- In social networks, using a broader approach, the chain of relationships is consistently spread and extended.
Taken as a whole, either approach is capable of bringing growth to self-media. Self-media on social media is, relatively speaking, more dependent on the overall volume of users. And the emergence of self-published content allows users to build a social relationship with self-published media through their content, a relationship that is stronger than that built on content from any other user, but weaker than that built on content from headline media or KOLs.
Communities with more egalitarian content interactions have in fact limited users and content, so self-media is more of an overlap of existing relationships for communities rather than bringing new ways of interacting.
At the same time, the chain of relationships in social networks adds trust to the information born from self-media, thus allowing for a more effective and rapid dissemination of self-media content. Because of this, the combination of social networks + self-media carries with it some of the attributes of social media.
As the content continues to grow, it contains more and more dimensional areas. The demand for a certain type of content and the need for timeliness in accessing content is also increasing, which also further drives the segmentation of content.
At the same time, the original user organisation has been further subdivided and fragmented, giving rise to smaller circles and groups. Groups are often based on people, and if the core people stop giving, the life of the group will gradually die out.
As the content becomes more intensive and the frequency of interaction with people becomes higher (in real time or near real time), the form of media changes.
If people interact deeply with information from the real world, it will be in the form of live streaming, while if they interact deeply with information from the virtual world, it will be in the form of gaming.
Compared to content in media, communities and social networks, content in games will give users a higher density of information, deeper and more frequent interactions. Of course, games also require more investment and take longer to produce, which is more similar to film and animation.
This kind of creative content requires people to not only digitise the real world in some way, but also to create native content in the virtual world and then combine the two to form new digital content.
Digital content far surpasses content originating from the real world, both in terms of volume of information and editability. They are not just graphic or video streams, but dynamically interactable content that can be accessed in real time, which inevitably places higher demands on people’s productivity.
From the perspective of content, the form of different media such as text, images and short and long videos determines how content is presented and, in the case of media, communities and other product forms, influences the relationship and interaction between users and content.
The various media, communities and social networks at this stage generate huge amounts of content every day, so that even information disseminated based on social relationship chains can no longer ensure that it is what one wants to see, and thus people are starting to use machines to analyse user preferences and to make information go to people more efficiently.
Creative content and gaming content both have structured data, which in the long run provides the basis for people to use machines to generate content. In the nearer future, machines will collaborate with users to generate more dynamic and rich content.
II. The Development Logic of Content Generation
(1) The Different Stages of Content Generation
The evolution of cloud and AI technologies has led to a subtle but important shift in the way social and entertainment is delivered: from traditional interactions that unfolded in an event-centric manner to spontaneous human-centric interactions.
With the proliferation of user-generated content (UGC) and AI technologies becoming tools for creative realisation and the process itself, we are also unlocking new types of media, social, community and gaming experiences as we create content using new methods.
If we consider the volume of content, how it is produced and the main forms in which it is presented at the same time, we can obtain a structure such as this.
In fact, we are currently in stages 1 and 2 above. Most of the current TV, film, music and games in the entertainment industry have been created by large professional creative teams. These products have been developed for a single-player experience, which means that: as we add users to the product who are also engaged in content interactions, these experiences don’t actually change.
As mentioned above, most of the content in the current market such as media, streaming and non-sandbox games fall into stage 1, while content such as self-media and sandbox games fall into stage 2, and social media, social networks and communities in a broader sense will straddle both stages 1 and 2.
Of course, ABC technologies (AI, Big Data, Cloud) are already being gradually applied to the industry to assist people in generating digital content more efficiently within certain rules and constraints, which is what stage 3 describes as content generation.
Powered by AI, Cloud and Big Data, this part of the content will be naturally dynamic and therefore able to accommodate the dynamic experience of multiple people at the same time.
The fourth part is the generation of a large and rich amount of content entirely automatically by AI, thus supporting the content-consuming needs of users in the Metaverse.
GTA 5 was developed over a five-year period, with a total estimated financial investment of $266 million and over 1,000 developers involved in its production. The Metaverse, on the other hand, will likely be millions of times larger than GTA 5 and still have dynamic multiplayer interaction in real time. Therefore, the metaverse must use AI for content generation in order for it to be created and run continuously.
Looking at the development spectrum of real and virtual worlds, stage 123 is all part of the digitized real world, while stage 4 is entirely the native virtual world.
(2) Co-create with AI
We know that both media and communities rely on the digital content produced by users.
In order to generate this content in a faster and differentiated way, computer vision technology allows us to quickly transfer information from the real world, by means of photos and videos, to the digital world and, with the help of computer graphics technology, we can see this content on any screen.
In stages 1 and 2, only a small number of people are producers of content (relatively speaking). But AI can democratise the generation of content, further lowering the barriers to content creation and making it much simpler.
With the assistance of AI tools, more people will become creative workers. We are able to convert specific instructions, images and logical processing into production-ready assets in a lightweight and modular way, thus greatly reducing the burden of coding, drawing, animation and other tasks.
We know that logic is the basis for decision making, and that speech, movement and hearing are the objects for the transmission of this basis; while text, images and music are the media, which we can digitally present on the screen. The digital content that machines can generate is therefore divided into logic (RL/SL/USL), language (NLG+TTS), and action (MG+CG).
OpenAI’s GPT-3, released this year, supports multimodal human-machine interaction and learns very dynamically to generate text that far exceeds the performance of GPT-2. And TTS, NLG, MG, etc. are enabling machines to generate corresponding media.
At the same time, AI is able to quickly learn the content of a script by understanding information from a game or movie script, generating a plausible plot line as well as dialogue and translations of the corresponding NPCs within the given constraints.
In fact, the point of difference from general AI is that while it may seem that the game or movie is very ambitious, the script may in fact be a few hundred pages long and the amount of information it contains is acceptable.
Given a framework of knowledge, AI becomes able to gradually understand the creator’s intentions and not only control the different reactions of NPCs to user interactions, but also create personalised encounters and dynamic episodic content together with the user.
In addition to this, if one looks at episodes or narratives as broad content, one can, with the assistance of AI, upgrade existing graphic and video content into real-time interactive content. Everything in content, whether objects or avatars, will gradually become “interactive”.
Traditional digital content does include the digitisation of people, so that we can use digital images and interact with content in the virtual world.
When an intelligent body created by AI can actively participate in the changes of the virtual world and interact with the real world, it becomes an “avatar”.
Since avatars are themselves digital content, when “avatars” with a certain level of intelligence emerge, they are able to produce and change a certain level of digital content on their own. This changes the relationship between the production of media and the supply of and demand for content.
With the help of AI, the content produced by these ‘avatars’ will be more real-time and scalable than that produced by real media practitioners. Therefore, the first change will be in the form and content of social media. Secondly, changes in the content of social media will lead to changes in the organisation of users, and therefore in the social relationships.
On this basis, when we build social relationships in the real world, it is likely that when a “virtual person” interacts with another “virtual person”, it brings up both sides of the real world, thus creating new social scenarios and new social networks.
The data that AI learns is not only structured, but also strictly egalitarian.
So for the ‘avatars’, the topics, content and domains of the community can be completely mastered and generated by them. We can imagine how real people would interact with content generated by avatars in a community of avatars. If this content is derived from games, can we directly enter the game and play against the virtual users in the community? Does this open up new game entries and scenarios?…
In fact, in addition to generating decisions on the logic side, AI needs to pass on this type of higher-level instructions to images to make them move in response to human interaction. Deep learning can be instrumental in making the movement of AI-controlled characters more coherent and smooth, and one can make them behave differently by adjusting various parameters as they move.
Furthermore, people are also experimenting with AI to generate digital music and art. OpenAI has released the music generation system Jukebox, a neural network system. Using different genres, artists and lyrics as input, Jukebox is able to output samples of new music created from scratch. For art, it is common to refer to art generated using GAN technology collectively as GANist art (GANism).
In 2018, Adobe hosted a launch event that literally demonstrated how AI can be used in art and design. Whether it was the intelligent keying implemented by Fast Mask, Moving Stills that can generate dynamic videos from still images, or the automatic generation of various art fonts, etc., it all left designers and artists nowadays with their jaws on the floor.
III. How does Consuming Technology Change Content Generation?
(1) Creating more interactive media content
Almost all current media already have digital products, and traditional paper media have electronic versions, while they have also pioneered new media distribution methods, incorporating text, images, and long and short videos into their content through digital creation.
For media with independent sites, it is almost a must to choose the platform where users gather at the moment. Whether it’s we-media or social media, the core proposition as a media is: how to use less input and expense in exchange for big communication impact?
And any platform with media properties will consider the next question: how to help creators improve the efficiency of content output while maintaining content differentiation?
In fact, in the graphic era, platforms basically provide rich text editors; while in the (short) video era, the strength of the platform’s tool attributes determines the richness and efficiency of the content users can generate using it.
The core of video lies in visual effects, so computer vision technology can fully realize its potential in this field, allowing a variety of visual effects to be added to recorded videos or live streaming in a simpler and more effective way.
The tools accumulate the initial users for the platform, and then by precipitating their content and distributing and pushing it through algorithms or other mechanisms, a content product with media properties emerges.
Whether such a content product is going to be social media or community oriented has to be judged based on whether the content and interaction is biased with the user or the content itself. If it is the user, it is a social media attribute; while if it is the content, it is community oriented.
For the medium, the video is followed by an immersive experience of real-time interaction, or the interactive object of the content becomes an intelligent body in the virtual world. Since games are the most interactive and immersive among digital content, the former approach is more likely to be a real-time gaming community, or bringing gamified interaction to media products.
The latter is due to the fact that avatars themselves are digital content, and when “avatars” with certain intelligence emerge, the relationship between media production and people’s supply and demand for content will change because they can autonomously produce and change a certain level of digital content, which brings new interactive relationships.
At the same time, we can also see that the threshold of creation and distribution mechanisms, from traditional TV content and news media to now short videos and content as media, are becoming more and more automated and lightweight. This is a credit to technology, which makes content generation and distribution smarter, thus unleashing users’ content creativity and allowing everyone to create real-time interactive content in a very convenient and efficient way.
In terms of interactivity, YouTube’s interaction is more like moving the traditional TV remote control to the screen.
Although UGC has brought a lot of content to YouTube, the interaction between users and content is still based on the traditional “search + recommendation” logic.
As the benchmark of long-form video, YouTube is a video site that almost doesn’t have to pay internet fees because its biggest advantage is actually the free bandwidth provided by Google Peering for YouTube. From professional media journalists to anyone on the street who wants to create and share content as video over the Internet, YouTube gives you HD, high bitrate, and high throughput technology no matter how long the video is.
As a result, YouTube is purely post-paid for content creators, and it hardly ever pays high sign-up fees directly for high-value content producers, as is the case with domestic video sites that go beyond their share plans with creators.
And can the logic of YouTube be used to reproduce it in China? The answer is actually pretty obvious. In China, bandwidth, cloud and other data costs cannot be reduced in the most straightforward way by companies, so either the length of content is limited or other ways of commercialization need to be used.
We can also see many media and communities that are video oriented start with a story of burning money to accumulate users and then commercializing them to cash in. But not all companies can make this story come true, because it is not only related to technology, but also to the interaction between users and the content itself.
For TikTok, short videos do provide a significant reduction in bandwidth costs, while also incorporating real-time interaction into the user viewing experience, rather than limiting the user’s interaction with the content to comments, as is the case with graphics. Users can scroll and browse through videos at will and interact with their favorite videos quickly and easily.
In fact, TikTok fundamentally changes the way we think about content, and content will no longer be something we passively receive. The simple and immersive interaction with the extremely powerful recommendation algorithm enables us to experience the world of content created by different people without interruption. Once you don’t like it, you can quickly pull away and the system will re-recommend the content.
If we look at TikTok not as a media or community, but as a kind of gamification portal, it leads not only to various digital real worlds, but also to the native virtual world. Long videos and short videos are different forms of interaction for different categories of content, except that short videos are able to actively interact with users at a faster refresh frequency.
We can also see that when users are producing this type of video content, they use various image and visual techniques to quickly differentiate the content. These technologies, or visual effects, also carry social attributes when assisting in the generation of individual content, and everyone can use such effects to share different content.
In other words, when generating content, technology can create more ways to interact between content and users, further increasing the diversity of content. At the same time, technology can make the interaction between users and content more dynamic, constantly creating content that players will enjoy.
The nifty point is that whether it is a long or short video, users may not be able to experience dynamic content generation in a particular video content, but they can constantly feel the dynamic appearance of different content in the same theme, music and scrolling playback.
Making users feel dynamic interactions on the outside of the content is actually what technologies such as recommendation algorithms enable.
If users want deeper dynamic interactions inside the content, then we need technologies to understand the logic of the content, not just to make it different at the visual and image level.
This requires more AI technologies to achieve: decision generation on the logic side and dynamic interactions between logic and image actions.
When the logic of content generation is implemented, we can assume that this logic and decisions can support personalized and dynamic interactions between users and any video or even live content in real time, continuously bringing users a more immersive content experience by automatically generating content and extending the depth of content.
Interestingly, content with highly dynamic and personalized interactions is what we call: a game.
(2) Constant gamification of content and social relations
In this era, with the continuous digitization of the real world and the proximity of the native virtual world, people’s entertainment is gradually shifting from offline to online pan-entertainment products. As one of the most important forms of entertainment for the modern public, games have become the new mass communication media after text, pictures and videos.
Digital technology makes games evolve from a kind of physical media in the real world to digital content with interactivity. Games as content have a high density of content as well as free interaction, allowing players to happily surrender their time in different mechanisms and play styles.
Content as a game, or “gamified content”, refers to the application of game mechanics and gameplay to other areas to guide users to interact more deeply with the content.
Compared to other media, games use the most advanced technology to engage viewers and players and give them an immersive interactive experience that goes far beyond text, images, and video.
In fact, games can encompass almost all forms of digital content interaction, while we can think of video as non-interactive game footage, images as a static frame in a game, and text as a game script or a description. Although such a description would have some cinematic elements, digital games and movies are moving in the same direction.
Unlike movies that show the will of the director or screenwriter, games have represented personalized interactions and experiences since the first day they were born. The constant breakthroughs in technology, while making games themselves more and more immersive and free, have also brought the interactive and social potential that games contain, to other industries.
With the emergence of games such as Fortnite, Roblox, and King of Glory, the next generation of games will not only be games as content, but will become more of a new vehicle for social relationships.
Users will be able to personalize their creations in the game, making their own episodes, characters and other experiences and sharing them with others. Two people who are completely unknown to each other in the virtual world will socialize and engage in other behaviors while experiencing game content together, which provides a constant stream of new scenarios for next-generation consumption.
It is worth noting that in the ongoing move towards a fully AI-driven Metaverse, the next generation of games and content will be driven by both AI and people. At the same time, the way we socialize will change because of the content generated by AI.
We will turn to our own needs when it comes to getting more content supply.
If, as in the real world, our daily encounters are not set in advance and are based on a number of independent and random events that drive our exploration, in the virtual world represented by games, we are free to explore virtual content with our friends.
In the past, when we met new friends on various social software, we would invite them to play games together and thus enhance our relationship; but now, more often than not, we meet new friends directly in games and socialize during the process of experiencing them together.
In-game socialization happens very naturally, and users no longer need to force themselves to be social. Everyone has their own role and status, and the game itself provides a variety of scenarios and topics that provide a ready-made social environment for users.
Users need to connect and interact with other players and avatars in order to achieve their respective goals.
At the same time, AI can assist us in personalizing the generation of scenes and plots, providing us with the necessary environment and motivation for social interaction, in addition to creating avatars in the digital world, bringing us new social relationships and corresponding scenarios.
In fact, except for the top celebrities, most celebrities do not even have as many fans as the characters in virtual contents such as games and comics.
AI technology, represented by reinforcement learning, can use the behavioral data of players in games for training and iteration in the foreseeable future, thus enabling the creation of truly intelligent virtual characters in a limited pan-entertainment field and bringing new social experiences.
Last but not least
As Jon Lai of a16z puts it:
“Yet the most exciting part about the Metaverse is not how we build it technically, but rather its potential to change the way we socialize with one another.”
Technology will bring new social relationships for people in the virtual world, and new production relationships.
The volume of automatically generated content is exploding at an accelerated rate. The current era of PGC and UGC will soon be over, and humans and AI will work together to create more dynamic, rich and personalized content.
The concepts we think of today as media, games, and social will be replaced by new concepts in the near future, and social interactions in the virtual world will have a randomness and serendipity more similar to that in the real world.
If there is such a question: In which field is the meta-universe most likely to happen?
From a contemporary perspective, perhaps it is the gaming industry; with the support of technology, when gamified dynamic interactive content emerges in various industries, we will find that it is actually the whole society that is moving towards a meta-universe together.
In fact, we can also see “society” as a content product composed of people and life, which is a product that will always be universally needed. As technological advances are able to meet new needs, the product will of course need to be iterated and updated.
While we desire to be connected, we are also constantly trying to go beyond the connection itself.
About rct
rct was founded in 2018, a member of Y Combinator W19, and is comprised of talents across AI, design and business. The team is passionate about using AI to create next generation interactive entertainment experiences. Our mission is to help human beings know more about themselves. So far, rct is backed by YC, Sky Saga Capital, and Makers Fund.
See our official website：https://rct-studio.com/en-us/
