The proliferation of generally intelligent AI models is turning machine learning projects on their heads and changing the source of risk when building AI projects. Projects that used to require painstaking assembly of training data and the building, testing and refining of models can now be accomplished much faster and easier by using these shared models like the large language and vision models whose popularity has soared this year.
Embedding inversion attacks pull rich data back out of embeddings, including people’s names, medical diagnoses and much more. Original sentences can be recreated in theme, if not in exact words. There’s already open-source software available to conduct these attacks. Sometimes, an attacker won’t even have to use fancy attacks to get at the original data because the vectors often have associated data and metadata that ride along with them. The attached data often includes private information or even the original raw input used to generate the embedding.Developers are moving fast to adopt new technologies that make their applications more powerful, their businesses more intelligent and their jobs easier.
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