We asked Garry Walker. A founding member of TAGuild and a prolific digital artist experimenting in the field of image AI about his thoughts and feelings on the future of gaming given recent advances in AI.
Computer games have come a long way since their inception in the 1970s. From simple text-based adventure games to highly realistic, open-world games with stunning graphics and complex gameplay, the technology behind these games has advanced significantly. However, the future of computer games may hold an even more significant change – the use of artificial intelligence (AI) to create and develop games.
The idea of AI-created games is not a new concept. In fact, some researchers have already begun experimenting with using AI to generate game content, such as levels, characters, and even entire game stories. These AI-generated games have been met with mixed reactions, with some praising their creativity and uniqueness, while others have criticized their lack of polish and overall quality. Despite these criticisms, the potential for AI-created games is enormous, and it is likely that we will see more and more games developed using AI in the coming years.
One of the main advantages of using AI to create games is the ability to generate an almost infinite amount of unique content. With traditional game development methods, creating a new level or character can be a time-consuming and costly process, often requiring a team of artists, designers, and programmers. But with AI, this process can be automated, allowing for the creation of an almost endless supply of content. This can be especially beneficial for games with procedurally generated content, such as open-world games, where players can explore new and unique environments each time they play.
Another advantage of AI-created games is the ability to create more personalized and immersive experiences for players. With traditional game development, it can be challenging to create games that appeal to a wide range of players, as different people have different preferences and playstyles. But with AI, it’s possible to create games that adapt to the player’s preferences, such as adjusting the difficulty level, changing the game’s pace, or even creating unique storylines based on the player’s choices.
AI-created games also have the potential to revolutionize the way games are tested and balanced. With traditional game development, testing and balancing games can be a tedious and time-consuming process, requiring a team of testers to play the game multiple times to identify and fix bugs and balance issues. But with AI, it’s possible to automate this process, allowing games to be tested and balanced much more quickly and efficiently.
Despite the potential benefits, there are also some concerns about the use of AI in game development. One concern is that AI-created games may lack the creativity and artistic vision of games created by humans. While AI can generate a vast amount of content, it may lack the ability to create truly unique and innovative ideas. Another concern is that AI-created games may lack the emotional impact and connection that players feel with games created by humans.
In conclusion, the future of computer games is likely to be shaped by the use of AI. The ability to generate an almost infinite amount of unique content, create more personalized and immersive experiences, and revolutionize the way games are tested and balanced, all make AI a powerful tool in game development. However, there are also concerns about the potential lack of creativity and emotional impact of AI-created games. Nevertheless, as the technology behind AI continues to advance, we can expect to see more and more games developed using AI in the future, and it will be interesting to see how it will shape the future of the gaming industry.
ChatGPT, the powerful language model developed by OpenAI, has the ability to generate a wide range of text-based content, from natural language text to programming code. One of the most exciting applications of ChatGPT is its ability to generate Python code for creating 3D models in Blender, a popular open-source 3D modelling and animation software.
Blender is a powerful tool for creating 3D models, but it can be challenging for those without a background in 3D modelling or programming to create complex models. However, with ChatGPT’s ability to generate Python code, it is possible to automate the process of creating 3D models in Blender, making it more accessible to a wider range of users.
The process of creating 3D models in Blender using Python code generated by ChatGPT is relatively straightforward. First, you would need to provide ChatGPT with a description of the 3D model you want to create, along with any specific details or constraints. ChatGPT would then generate the Python code required to create the model in Blender. Once the code is generated, you can then copy and paste it into Blender’s Python console, and the model will be created automatically.
One of the main advantages of using ChatGPT to generate Python code for creating 3D models in Blender is the ability to create models that are highly customizable. With traditional 3D modelling methods, it can be challenging to make changes to a model once it has been created, but with Python code, it is possible to make adjustments to the model’s shape, size, and other properties with just a few simple lines of code.
Another advantage of using ChatGPT to generate Python code for Blender is the ability to create models that are highly detailed and precise. With traditional 3D modelling methods, it can be challenging to create models with precise dimensions, but with Python code, it is possible to create models with precise measurements and exact proportions.
ChatGPT’s ability to generate Python code for Blender can also be used to automate the process of creating animations. By providing ChatGPT with a description of the animation you want to create, along with any specific details or constraints, it can generate the Python code required to animate the model in Blender. This can save animators a lot of time and effort, as they no longer need to manually keyframe each movement.
While ChatGPT’s ability to generate Python code for Blender is powerful, it’s important to note that the quality of the code generated will depend on the quality of the input provided. The more detailed and precise the input, the better the code will be. Also, it is important to note that the code generated by ChatGPT is not guaranteed to work perfectly out of the box, and may require some tweaking and debugging.
In conclusion, ChatGPT’s ability to generate Python code for creating 3D models in Blender is a powerful tool that can make 3D modelling more accessible to a wider range of users. It can save time and effort by automating the process of creating models and animations, and it can also create models that are highly customizable and precise. However, it’s important to note that the quality of the code generated will depend on the quality of the input provided and the code may require some tweaking and debugging. As the technology behind ChatGPT continues to advance, we can expect to see more and more applications of this powerful language model in the future.
Whilst there may still be a long way to go before games are designed and written by AI all of the components needed to do so are progressing at an exponential rate. What was impossible only a few years ago is now in the hands of the mainstream public at little to no cost. Who knows where we will be in 5 years time?
In fact, you probably didn’t even notice that this entire article barring the introduction and conclusion was actually written by an AI without any human interaction. Scary, isn’t it?