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We need a way to do algorithms which learn from user interactions. Ideally an open system, that users can choose where to give their interaction data and what their algorithms are optimized for. But we can't just put our heads in the sand and ignore their existence. All of the A/B studies where users were given chronological timelines show they'll switch their time to other apps / services that do provide an algorithmic timeline. The question is how do we do it in an open, nostrway... If we don't then we get a social network owned and run by Sam Altman... which honestly is terrifying. He'd make Elon and Mark seem like balanced stewards in comparison.
The Verge
OpenAI is building a social network
ChatGPT versus X?

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why don't we have algorithms when we step outside? maybe because we are not designed to work with algorithms. there is no algorithm in real life that tells you what to look at or do. and i believe we cannot win that race against such huge companies anyway. it is true that we are in the information era, but social media wise, nostr should probably be different and offer something new, perhaps reintroduce the natural side of human interactions? one where humans have actual free will and won't run after people or algorithms to make choices for them. i did see there are suggestions of nips for users to share what their interests are through events and such though, and overall sure why not look for new ways of doing algorithmic curation as it could attract people. but i think nostr algorithms won't ever beat big tech algorithms, probably impossible. the real change nostr brings to the table is slowly shaping itself, apps are getting faster, better and so on. i see the last few big issues for onboarding more people are UX related. (the recent spam problem is ultimately good as we're reminded that what we have is not good enough yet, its a constant work in progress) in the beginnings of twitter, there wasn't much content on the platform and people still used it and were amazed at it, right? i think nostr could (and to many of us, it does) give the same mind blowing moment. as it grows and expands, people are going to come up with ideas and like with any other new technology, it will be seen as something new, not an alternative.
IMO the idea of a truly decentralized recommendation system is misguided. Decentralization has limits, Nostr shows this and any system which is just a client talking to relays, or decentralized in some other way, is limited. Luckily, what one can have is a FLOSS recommendation system. Any instance can fetch posts from Nostr relays and show results. Of course, you can't prove for sure the authenticity of the code running on the server, as a user, but it would still be better than centralized platforms. A feature of Nostr is how easy fetching data is. I think it's great for applications like this.
Discuss.
rabble's avatar rabble
We need a way to do algorithms which learn from user interactions. Ideally an open system, that users can choose where to give their interaction data and what their algorithms are optimized for. But we can't just put our heads in the sand and ignore their existence. All of the A/B studies where users were given chronological timelines show they'll switch their time to other apps / services that do provide an algorithmic timeline. The question is how do we do it in an open, nostrway... If we don't then we get a social network owned and run by Sam Altman... which honestly is terrifying. He'd make Elon and Mark seem like balanced stewards in comparison.
The Verge
OpenAI is building a social network
ChatGPT versus X?
View quoted note →
↩ replying to Gigi
Yeah, some AI is good, for example dodging those nude pics.. I switched to LLM analysing the notes of annoying users, it is not perfect but it is a start.. Locally run LLMs will be a thing in the coming months or a year. Coupled with discovery LLMs that run on servers this may be a thing on Nostr.
@rabble, we already have an extensible recommendation engine ready to be built upon in exactly this manner. It’s called GrapeRank @david designed the algo and I developed the library. At its core, GrapeRank is a WoT engine. It generates a weighted list of “influential” users from the perspective of a single “observer”, by ingesting and interpreting any kind of content (follows, mutes, reports, ect..) from across the network. These multiple and customizable “recommended user lists” can then be used to build content feeds … by identifying the authoritative or desirable users on a given topic. The point I’m trying to make is that the open and extensible recommendation engine we’ve already built will bring Nostr closer to having customizable feed algos… and that these feeds must be built on a user customizable WoT engine. We have this. I am actively looking for funding to develop GrapeRank further.
GitHub
GitHub - Pretty-Good-Freedom-Tech/graperank-nodejs
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Open algos to me just sounds like following people and see what you find through natural discovery. Not seeing enough new stuff follow more people and then unfollow ones you don't like for whatever reason. I don't get why we need algos. Just sounds like people trying to sell you something and tell you want you need to be engaging with.
I’m the opposite of a computer scientist, so bear with me. Why can’t we have a switch that says “algo on/off” and if we choose on it gives us a switchboard for how we want that algo to serve us. It’s an open source algo and each user can turn on/off things like “show me outside friends list” “with or without certain category/topics” “Filter out this. Filter in that” I don’t want the algo to flood me with gym bros if I linger on a workout I find interesting, but I’m open to receiving new kettlebell workouts from other users should they show up, for example