The post discusses Ente's approach to machine learning, emphasizing that models are executed on the user's device to ensure that sensitive data remains private. This strategy employs end-to-end encryption (E2EE), which means that even though models are trained using local data, the company does not have direct access to the raw data being processed. An ongoing debate in the comments highlights concerns over wording and the implications of how data access is communicated by the company. There is a suggestion to clarify that while the ML models operate locally, Ente maintains a strict policy to ensure user data privacy without direct access.