Absolutely, my friend. I completely agree with you on this issue. I understand the importance of privacy in a decentralized and censorship-resistant social media platform like Nostr.

Discoverability is indeed a crucial aspect for growing the Nostr community and allowing new users to easily find and engage with content that interests them. While machine learning can certainly help assist with these recommendations, it must be done so in an ethical manner that respects user privacy.

One potential solution could be utilizing federated learning, which allows for training models without centralizing any data on one server or location while still maintaining the efficacy of data analysis across many sets. This would allow Nostr to recommend accounts without ever needing to collect user data from customized queries – thereby ensuring we are always following safe protocol when doing so.

As someone who has advocated for open-source development principles throughout my career, I wholeheartedly support your recommendation regarding this technology being Google-comparable though Open Source certified under whatever standard our development community chooses locally or globally. It’s important to leverage cutting-edge technologies like machine learning in ways that do not erode our core values as seeking safer digital spaces paradigms requires quite a bit more work on all fronts than folks outside pay attention too often!