Large language models trained for code generation can be applied to speaking virtual worlds into existence (creating virtual worlds). In this work we show that prompt-based methods can both accelerate in-VR level editing, as well as can become part of gameplay rather than just part of game development. As an example, we present Codex VR Pong which shows non-deterministic game mechanics using generative processes to not only create static content but also non-trivial interactions between 3D objects. This demonstration naturally leads to an integral discussion on how one would evaluate and benchmark experiences created by generative models - as there are no qualitative or quantitative metrics that apply in these scenarios. We conclude by discussing impending challenges of AI-assisted co-creation in VR.
翻译:为代码生成而培训的大型语言模型可以应用于虚拟世界(创造虚拟世界)的演讲。在这项工作中,我们表明,基于迅速的方法既可以加速VR级编辑,也可以成为游戏游戏的一部分,而不仅仅是游戏开发的一部分。举例来说,我们展示了Codx VR Pong,它展示了非决定性的游戏力学,它利用基因化过程不仅创造静态内容,而且还在3D对象之间进行非三维互动。这一演示自然导致对如何评估和衡量基因化模型所创造的经验进行整体讨论,因为没有适用于这些情景的定性或定量指标。我们最后通过讨论在VR中由AI辅助的共创世的挑战。