卡帕西的鹈鹕
Karpathy’s Pelican

原始链接: https://twitter.com/karpathy/status/2083749667410727319

大型语言模型(LLM)近期的进步让许多曾经被认为不可行的创举成为了可能,例如让 Claude 3 Opus 根据《指环王》开篇的内容,程序化生成一整套 3D Three.js 环境。该模型利用巨大的 Token 配额,编写了 5,500 行代码来统筹复杂的 3D 资源和动画——由于工作量极其繁重,人类通常不会手动完成此类任务。 这种能力预示着未来我们可以按需生成“即时、高度定制的虚拟世界”,从而创造出类似于定制版《侠盗猎车手》(GTA)那样个性化、可游玩的体验。然而,这也凸显了当前一个重大的局限性:LLM 无法原生“观看”或与其构建的环境进行交互。由于模型无法实时测试或视觉化审核其作品,生成结果往往会出现“卡顿”或瑕疵。尽管其原始生成能力令人印象深刻,但在世界构建方面若想取得实质性进展,仍需模型具备更强的多模态感知能力,并能够测试自己的输出结果。

这篇 Hacker News 帖子讨论了 Andrej Karpathy 最近推广的“Pelican”,这一进展在社区中引发了褒贬不一的反应。 评论者们探讨了人工智能的发展轨迹,一些人指出我们正迈向一个由大语言模型(LLM)生成的超个性化、按需娱乐的时代。一位用户展示了一个利用 LLM 从电影场景描述中生成 3D 动画的项目,体现了生成式媒体的快速演进。 讨论还转向了人工智能的未来效用,有人建议该技术最重要的影响将在于自主制造——即从设计产品转向制造生产这些产品所需的设备。 在技术讨论之余,人们对 Karpathy 当前的角色表现出了明显的怀疑。一些长期关注者表达了失望,指责他为了配合当前雇主的营销目标,改变了以往对人工智能体(AI agents)客观、审慎的立场。其他人则继续关注更广泛的行业趋势,反思了现代 LLM 界面与曾经失败但富有远见的 Google Wave 平台之间的历史相似之处。
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原文

We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all. I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand. Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.

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