Grasping Concept Spaces

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Revision as of 16:11, 28 October 2024 by afb21 (talk | contribs) (Created page with "Client: Sam Henshall-West, JAID <sam.henshall-west@jaid.io> Today's most powerful machine learning models, including generative AI LLMs like ChatGPT, encode their knowledge as higher dimensional latent spaces. Vector-based concepts in that space can be clustered as regions on a 2D screen, for example using the t-SNE visualisation algorithm. Your task is to create a 3D version of t-SNE that is interactive, so users with VR headsets can literally “grasp” a concept, an...")
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Client: Sam Henshall-West, JAID <sam.henshall-west@jaid.io>

Today's most powerful machine learning models, including generative AI LLMs like ChatGPT, encode their knowledge as higher dimensional latent spaces. Vector-based concepts in that space can be clustered as regions on a 2D screen, for example using the t-SNE visualisation algorithm. Your task is to create a 3D version of t-SNE that is interactive, so users with VR headsets can literally “grasp” a concept, and manipulate it to query, fine-tune, or adjust the machine learning model.