<ul><li>Dynamic Weight Inversion (DWI) is a technique that allows modulating the embedding space in real time based on specific intent or context.</li><li>This technique reshapes the semantic space to accurately reflect the user's intent, enabling the system to find what is meant, not just what's superficially similar.</li><li>The DWI approach involves calculating a transformation matrix based on the input vector and the target vector representing the desired context.</li><li>DWI has been successfully tested on a semantic search engine without retraining the model, showing significant changes in similarity rankings based on different contexts.</li></ul>

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