Text by: Kasou Kazoku
In the world of Web3 games, we are witnessing some challenging times. From 2018 to 2023, a total of 2,817 Web3 games were launched, but sadly, 2,127 of them (75.5%) failed to succeed, highlighting the difficulties of the industry.
Although Web3 games have not really set off a craze since 2018, they are often highly anticipated every time cryptocurrency opens a new chapter. Combined with the current bull market expectations, we are likely to see many games reach crazy valuations.
Just looking at 2024 and 2025, with the concentrated outbreak of many AI models such as DALL-E, Stable Diffusion, Midjourney, ChatGPT, we believe that "AI penetration into Web3" will become its key driving force. Based on AI technology breakthroughs, in July, DeGame officially announced the launch of the "AI generated game" function, hoping to bring a new attempt to the strong recovery of the Web3 game industry through a series of interoperable, composable, programmable and tools, as well as modular game/video/voice generation models.
With nearly 3 billion Web2 gamers and nearly 600 million Web3 users worldwide, Web3 games have a strong narrative foundation. However, at present, funds and projects are more concentrated on the infrastructure level, lacking new growth points in large-scale user adoption and conversion narrative.
The key to promoting the development of the gaming industry actually lies in technological change. The application of AI technology in game development is becoming increasingly mature. Using AI to generate models to solve typical problems faced by Web3 games, thereby achieving breakthroughs and growth in the short term, may be the best solution.
Ice-breaking Narrative "Ice Age"
Playability was the main drawback that limited Web3 games from attracting large numbers of players. The monotonous gameplay and rough graphics often made players flash back to more than a decade ago when playing Web3 games. But for ordinary players, there is only one hard standard for evaluating the quality of a game, that is, whether it is fun; Web3 games that focus too much on "Fi" can only attract gold-making people, but cannot complete the large-scale conversion of Web2 users.
But from a practical perspective, as an extremely time-consuming and expensive industry, the explosion of the gaming sector requires the joint promotion of multiple factors such as capital, time, and technology. When time moves to 2024, AI seems to be able to bring these factors together. The improvement of modular AI generation tools has provided stronger support for Web3 games to improve towards 3A-level production and high quality.
In traditional games, NPCs (non-player characters) have very limited artificial intelligence and can only operate in fixed situations. With the help of AI technology, NPCs can simulate human behavior more realistically and have more intelligent operation methods. For example, the AI NPC real-time dialogue decryption in "Save Me! Labor Law Guardian" increases the interactivity and immersion of the game.
In addition, AI can also be used to generate environments, character images, and numerical balance, further enriching the diversity and playability of games and making in-game interactions more convenient and natural. Traditional game interaction methods are often based on keyboards and mice, which are difficult to meet the needs of players. With the help of AI technology, more intuitive and vivid interaction methods can be achieved, such as voice, gestures, expressions, etc.
In general, the biggest direction of successful practice of AI in the gaming field is undoubtedly to enhance the gaming experience and personalize the gaming content. The AI generation model can optimize the game development process in a short period of time, integrating the multiple highlights of traditional Web2 games at a lower development cost, so as to improve the smoothness of incremental user participation in Web3 games, which is an important part of the large-scale migration of Web2 users to Web3 games.
Unleash your creativity
Decentralized blockchain is an important force in balancing AI (and machine learning). First, it can be combined with other technologies, such as ZK, to optimize the trust framework of machine learning. Second, it can effectively utilize long-tail resources to reduce the cost and threshold of using AI. On the other hand, because many Web3 applications sacrifice user experience for security and decentralization, AI can help optimize and improve user experience. This is the part where AI can empower Web3.
Specifically in terms of application scenarios, although AI+DeFi and AI+DID/social both have use cases, generative AI is naturally applicable to text, sandbox, development, open world, UGC and other gameplays that are familiar to Web2 users. Rewriting the game logic through AI and making the game more uncertain and random will make Web3 games and AI collide with different sparks.
For example, an important innovation of Web3 games is that it requires users and platforms to participate in the creative process together, rather than a planned finite game. In the game, there is a concept of Lore. In traditional games, this is planned by game designers and is completely predictable. Through AI models, various inputs can be brought together to generate unpredictable outputs, so that the game has unlimited possibilities.
Imagine that one day in the future, we will be able to access a magical virtual world through AR/VR devices. We can use prompts to instantly create 2D and 3D objects that we can imagine or cannot imagine in our minds, just like reciting a magical spell, and then we can truly own them (data is hosted on the public chain). We can also interact with the intelligent AI NPCs in the virtual world and influence the development of the story of the entire game world, and all of this will be supported by a completely transparent open source infrastructure.
Under this vision, AI-driven Web3 gaming will unleash unlimited creativity.
Rapid evolution and continuous integration
In fact, the history of AI game development may date back even further.
The use of AI in game development can be traced back to classic games such as "StarCraft" and "Diablo". At that time, developers needed AI systems to create interactive virtual worlds and characters. These systems have become standard configurations for the development of such interactive platforms.
Early research related to game development AI emphasized controlling non-player characters (NPCs), and with the development of natural language processing (NLP) technology, some pioneering work has emerged using deep learning technology to generate levels.
The representative work is MarioGPT, which successfully generated some levels in "Super Mario Bros." through a fine-tuned GPT-2 model.
With the rapid iteration of models, AI is becoming more and more powerful. For practitioners in the Web3 gaming field, how to use AI to better create high-quality games and how to apply AI-generated models to the R&D process are the core of grabbing incremental users.
DeGame AI is a lightweight generative model and a code-free creator tool that supports users to integrate the tools provided by DeGame AI into the existing game production ecosystem during game development or optimization to automatically perform challenging content creation tasks. At the same time, based on the Transformer neural network, through DeGame's Annotation and Substation models, DeGame AI also provides functions such as text-generated game videos.
We expect to see emergent, procedurally generated worlds, each with its own rich history, inhabitants, and mysteries. There will be interactive fiction, where the story evolves through the player's choices and is told through generated images, video, and audio, bringing more possibilities to Web3 games.
Final Thoughts
If a Web3 game practitioner wants to complete a game, he must at least cover interactivity, playability, and content with a core game plot, consider the plot connection between the characters in the game, and carefully design the game levels and goals for the players. With the help of cutting-edge AI generation models, creativity and imagination can be transformed into complex game mechanisms and storylines, and AI NPCs with vivid personality traits can be designed to lead the player's actions, trigger the direction of the game story, and improve the efficiency of game development and operation, reduce the cost of game development and operation, and thus generate new profit growth points.
AI technology has many applications in the development and operation of games, including game plot planning, map generation, level setting, task generation, dialogue generation, story narration, model generation, and the generation of rules such as in-game growth systems and economic systems.
It’s just the beginning, and we believe that exploration in the field of AI and Web3 games will open the door to a new world of games. As technology advances and its applications deepen, players can expect to encounter more unique gaming experiences that will go beyond the boundaries of traditional games and bring a more immersive and interactive gaming world. This is an exciting era for players who love games and technological innovation.
