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uh the buzz surrounding binary quantization has been impossible to ignore especially if youamp;#39;ve been keeping tabs on recent discussions in Tech circles and the concept itself isnamp;#39;t new but whatamp;#39;s reignited interest is the announcement from cohere regarding their latest support enhancements for intap and binary embeddings in their coher embed me3 uh first letamp;#39;s quickly see why we need embeddings uh embeddings are one of the most versatile Tools in natural language processing uh supporting a a wide variety of settings and use cases um in essence embeddings are numerical representations of more complex objects like text uh images audio Etc um specifically the objects are represented as n-dimensional vectors um after transform the complex objects you can determine their similarity by calculating the similarity of the respective embeddings uh this is crucial for many use cases it serves as the backbone for recommendation systems retrieval oneshot or few shot l