为什么没有人工智能游戏?
Why No AI Games?

原始链接: https://franklantz.substack.com/p/why-no-ai-games

## 缺失的AI游戏革命 尽管最近AI,特别是大型语言模型(LLM)取得了显著进展,但真正突破性的AI驱动游戏体验仍然难以捉摸。AI正在影响游戏*开发*,但尚未*定义*游戏玩法。早期实验,如AI Dungeon、Death by AI和Suck Up!——主要依赖于对话式AI——未能获得持久的玩家兴趣。即使是技术上令人印象深刻的演示,如AI生成的3D世界,也感觉平淡无奇。 作者认为这并非仅仅是缺乏尝试。商业模式受到依赖昂贵第三方AI服务的阻碍,并且一部分玩家积极抵制生成式AI的整合。然而,核心问题可能更深层:LLM本身并不*有趣*。 传统游戏从简单、确定性的规则中获得乐趣,这些规则创造了涌现的复杂性。AI的“软逻辑”感觉太像与人互动——引人入胜,但并非本质上具有游戏性。作者现在认为游戏的魔力在于精心设计的约束,而不是从无限、不可预测的生成开始。尽管持怀疑态度,他们仍然希望能够出现真正创新的AI游戏,但会以更务实的视角看待。

## 为什么AI游戏不多? 最近Hacker News上的一场讨论探讨了AI在视频游戏中的存在感为何出乎意料地有限,尽管大型语言模型和生成式AI取得了进步。 几个因素导致了这种情况。交互式AI的高成本、工作室之间缺乏数据共享(尤其是在3D资产生成方面)以及游戏开发者自身的抵制是关键障碍。 完全由AI驱动的游戏很少,但AI辅助存在潜力。 例如,可以使用AI为程序化生成增加复杂性(如《无人深空》),或增强NPC互动——《上古卷轴5》的模组已经展示了这一点。 然而,性能限制和对高质量语音合成的需求仍然是重大的技术挑战。 讨论还强调了游戏社区和行业内的文化抵制,人们对“AI艺术”表示担忧,并且更喜欢传统的手工制作体验。 尽管如此,一些人认为小型独立开发者更有可能率先采用创新的AI游戏玩法,并可能带来定义下一代游戏类型的作品。 最终,AI融入游戏仍处于早期阶段,需要时间和进一步开发。
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原文

Here’s a puzzle — back in 2021, when the new AI era was just kicking off, it seemed obvious (to me at least) that it would lead to new kinds of games and radically new forms of gameplay. But here we are, 5 years later, and we haven’t seen anything to speak of. Clearly, AI is having a huge impact on how games are developed (like it has for all software), but there haven’t been any significant new AI-based game experiences. What gives?

Maybe I’m exaggerating. Maybe there are some cool AI-centric games that I’m overlooking? Let’s see…

To be honest, that’s the only one I had even heard about. But apparently there have been a couple of other semi-successful ones…

There have also been a handful of semi-viral demos of AI-powered game “engines”. There was one that was a sort of Drunk Minecraft and Google has one called Genie 3 which seems technically impressive but also seems kind of boring. Even if it is capable of generating a reasonable facsimile of a stable, coherent 3D space you can move through and interact with, there’s nothing particularly mind-blowing or novel or interesting about these spaces. They just look like clunkier, sloppier versions of run-of-the-mill video games.

Am I asking for too much here? I don’t think so. Video games’ main job is to blow people’s minds. They are extremely good at highlighting the things that are amazing about computers. I distinctly remember the shudder of sublime metaphysical weirdness that went through me the first time I played DOOM on a LAN and turned the corner and saw another person who was inside that imaginary space with me. I remember having my mind blown by MYST. I remember my first encounter with the linguistic magic of Infocom’s parser-based adventure games. I sometimes feel some of that magic when interacting with LLMs, but nothing remotely like that from any of these AI games.

Thinking about this topic made me realize that something similar was true of AI in games in general, separate from the question of these new models. There just aren’t all that many examples of games where interesting AI is the hook. There’s The Sims, of course, but is that even really AI? There are those Orcs in that one Lord of the Rings game who hold grudges against you. There’s the alien in Alien Isolation. The creature in The Last Guardian. The enemy soldiers in Fear? The creature in Black & White? The bickering couple in Façade? Am I missing any big ones? Doesn’t it seem like there should be more?

Let’s hold off on that question, and return to the main puzzle. Why hasn’t this miraculous new version of computational magic given us a single truly groundbreaking game?

The first two are prosaic, practical issues and the third is a “design theoretical” speculation that I think explains what’s really going on here.

  1. Business Models. It’s very hard to build a real game around core functionality that you are paying a third party to supply. I’ve built prototypes that were reasonably fun but there was no way to actually release them that made sense. Charge players a subscription? Some kind of microtransactions? Ironically, when it first launched, Death by AI nearly went bankrupt due to OpenAI/ElevenLabs costs. This dynamic also discourages developers doing small experiments and releasing them for free, hoping to go viral. The incentives are all wrong. Developers are highly motivated to hit the model as little as possible, to use cached, pre-generated responses or find other workarounds. I’ve also built game prototypes where the whole experience changed dramatically, for the worse, because the model I was building around changed in ways I couldn’t understand or control.

  2. Culture Wars. The video game audience has decided, almost unanimously, that they don’t want generative AI in their games. This might eventually change, but as of now it is a well-established, non-negotiable taboo.

  3. The Nature of Fun. But I don’t think either of the first two reasons would be enough to prevent a truly compelling new game experience from making itself known. I think what’s really going on here is that these new models just aren’t the natural source of fun I thought they would be when I first encountered them. Some forms of computation end up being a deep well of fun. 3D rendering is fun. Physics engines are fun. But these new AI models, despite being powerful and useful and fascinating, don’t seem to be intrinsically fun. Which I think is kind of surprising!

Years ago, when I first started playing around with the new models, I thought their messy, organic, stochastic qualities could be the key that unlocked whole new categories of gameplay. The story I told myself was that traditional video games were overly “mechanical” — they relied on brittle, deterministic logic and formulaic “lock-in-key” behavior. I thought that, if we embraced the psychedelic weirdness of these new models, we would discover a new kind of dream logic that would support wild new kinds of surreal game experiences. I think I was wrong.

The past few years of playing around with these things, which ranged from little experiments to full-scale commercial projects, has left me with a new-found admiration for the brittle, deterministic, mechanical logic of old-fashioned video games.

You know what’s fun? A stick. A stick is fun. A ball is fun. I now have a (hopefully) more nuanced appreciation for the way that the fun of games is rooted in simple behaviors and deterministic rules. The fun of games is deeply connected to the miracle of emergence, in the ways that a small set of seemingly trivial constraints interact with each other to produce an infinite expanse of surprising complexity. Starting with a bunch of surprising complexity doesn’t lead to even more fun, it just short-circuits the whole process.

The soft logic of generative AI is too much like the soft logic of other people. Other people aren’t intrinsically fun. They’re sacred and profound and fascinating and beautiful but they aren’t, by themselves, fun. That’s why we have games!

I guess I should have seen this coming. I knew the best way to understand these models was as simulators, and I may have fallen into a version of the immersive fallacy.

I’m sure that, even as I type these words, there is a clever teenager somewhere proving me wrong. I certainly hope so. There’s no way this crazy new form of computation won’t eventually lead to some wild new kinds of gameplay, and I fully intend to keep messing around with these things looking for it. Only hopefully now with less panicked urgency and a slightly sharper eye.

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