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Because they enable you to involve things typically unrelated (i.e. two types of embeddings), think and understand and manipulate them in a simpler mathematical
by authorfly 2y ago
Because they enable you to involve things typically unrelated (i.e. two types of embeddings), think and understand and manipulate them in a simpler mathematical model (a single vector) and see how you can then apply the most fundamental mathematical operations (e.g. cosine similarity) in terms of simpler outputs/metrics. It enables a form of creativity in other words; it makes you see things like the math in Transformers in a less anxious light as you understand how these things can overlay into a simpler intuitive understanding.
- redwood 2y agoSounds similar to the power of LoRa; critical building blocks to building efficient scalable serving