> How can Slack guarantee that the model won't incorporate proprietary insights on sourcing the best foobar producers into its choice of the next token? This i

> How can Slack guarantee that the model won't incorporate proprietary insights on sourcing the best foobar producers into its choice of the next token? This is explained literally in the next sentence after the one you quoted: "We protect data privacy by using rules to score the similarity between the typed text and suggestion in various ways, including only using the numerical scores and counts of past interactions in the algorithm." If all the global model sees is {similarity: 0.93, past_interactions: 6, recommendation_accepted: true} then there is no way to leak tokens, because not only are the tokens not part of the output, they're not even part of the input. But such a simple model could still be very useful for sorting the best autocomplete result to the top.