Matryoshka Embeddings with Aditya Kusupati, Zach Nussbaum, and Zain Hasan - Weaviate Podcast #89!
Weaviate Podcast
Information Diffusion Argument and Dimension Importance
According to the information diffusion argument, all dimensions between 33 and 64 are equally important because they do not have an importance loss. By adding dimensions incrementally, each chunk contains enough information to interpolate between the dimensions. This approach allows for utilizing the initial advantage of higher information dimensions and obtaining utility while considering the marginal effects of the remaining dimensions. The diffusion of information evenly across dimensions is believed to be achieved through this method, explaining the reasoning behind log or exponential separation of granularities.
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