How is the cultural made computational? CLIP models are a recent artificial intelligence (AI) innovation which train on massive amounts of Internet data in order to align language and image, deploying this ‘grasp’ of cultural concepts to understand prompts, classify images and carry out tasks. To critically investigate this cultural codification, we explore MetaCLIP, a recent variation developed by Meta. We analyse the model’s metadata, a single file of 500,000 terms that aims to achieve a ‘balanced distribution’ or sufficiently broad understanding of concepts. We show how this model assembles histories, languages, ideologies and media artefacts into a kind of cultural knowledge. We argue this codification fuses the ancient technique of the list with a more recent technique of latent space . We conclude by framing these technologies as cultural machines that exert power in defining and operationalising a particular understanding of ‘culture’ invisibly and at scale.

中文翻译：

---

培养机：MetaCLIP 如何编纂培养

文化是如何成为计算的？CLIP 模型是最近的人工智能 （AI） 创新，它使用大量互联网数据进行训练，以对齐语言和图像，部署这种对文化概念的“把握”来理解提示、对图像进行分类和执行任务。为了批判性地研究这种文化编纂，我们探索了 MetaCLIP，这是 Meta 最近开发的一个变体。我们分析模型的元数据，一个包含 500,000 个术语的单个文件，旨在实现“平衡分布”或对概念的足够广泛的理解。我们展示了这个模型如何将历史、语言、意识形态和媒体人工制品组合成一种文化知识。我们认为这种编纂将 list 的古老技术与较新的潜在空间技术融合在一起。最后，我们将这些技术构建为文化机器，它们在无形和大规模地定义和实施对“文化”的特定理解方面发挥着力量。