@kyle
trying new things
Relays (5)
- wss://nos.lol/ – read & write
- wss://relay.damus.io/ – read & write
- wss://relay.primal.net/ – read & write
- wss://relay.snort.social/ – read & write
- wss://premium.primal.net/ – read & write
Recent Notes
2. Are they dumb? When we were in our teens even the dumbest had torrents and chat rooms figured out and that was much more technical than this
More of a time-to-value thing I think; how much time do I need to spend in order to get entertained?
Also a function of effort as well; generationally not very good at “seeking” things out, unless extremely motivated, due to usefulness of algorithms
Also a function of effort as well; generationally not very good at “seeking” things out, unless extremely motivated, due to usefulness of algorithms
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Why do we have such a low population of young people on nostr?
#asknostr
1: awareness
2: value prop and messaging is terrible, bad marketing overall
3: too much technical jargon at the forefront of most clients, needs to be abstracted
2: value prop and messaging is terrible, bad marketing overall
3: too much technical jargon at the forefront of most clients, needs to be abstracted
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Our apps need to just work and be fun to use.
The censorship resistance needs to be a "btw it's also decentralized" - it can't be the leading feature, nobody cares
nostr:nevent1qqs9gy4uv6hltw2jym2pc7...
Yep, there’s so many more appealing parts than censorship to normies, should be leading with those
Every 15 years, the tech industry "rediscovers" a thesis from the 70s - 90s, gives it a sexier name, and raises millions in VC funding for it
In this case, it's context layers for AI systems, which are 30 years old.
In this case, it's context layers for AI systems, which are 30 years old.
Sure, it's not inspiring but I'll share. I actually started from the bottom position in retail and worked up to account management role which I hated and led me to rejecting a chance with their corp e...
This can feel like such a niche place, so I’m always interested to hear somebody’s journey here and I’m somewhat inspired by everyone in a way as well! Appreciate you sharing your story and welcome
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Hello Nostr, if you have not read anything by Neil Postman, I highly recommend you do.
“Amusing ourselves to death” is such a fantastic read, and I frequently revisit it.
Has anyone built an agent on Nostr that doesn’t post, but strictly consumes/navigates to find interesting content, and surfaces it to you? I feel like LLMs can truly be “the great filter” and “the great curator” we need to no longer be inundated with endless feeds.
“Amusing ourselves to death” is such a fantastic read, and I frequently revisit it.
Has anyone built an agent on Nostr that doesn’t post, but strictly consumes/navigates to find interesting content, and surfaces it to you? I feel like LLMs can truly be “the great filter” and “the great curator” we need to no longer be inundated with endless feeds.
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back after a social break - wtf happened to nostr?
is this all because of openclaw?
is this all because of openclaw?
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What is UpScrolled?
A new alternative to TikTok that’s algo free, already has 1m+ users from what I understand
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Nostr quick fix that no one wants to do, looks like a shitpost but is probably real:
The major nostr clients shadowban all Bitcoin slogans, price chat, pfps, references, "memes", AI images, ai pfps, ...
I was working on something I thought would help but unfortunately had to focus on other things. Essentially wanted to use a combo of clustering algorithms + LLMs to topic model all of nostr and create topical relays and clients focused on particular types of conversations.
very similar to how subreddits work, but without any moderators. The clustering algos/LLMs would organize content based on embeddings (replacing moderators) and it would be much easier to find the stuff you care about without knowing who to follow.
clustering might be better bc it's not as "black box", but it's a great way to use machine learning without going down the recommendation algorithm slope
very similar to how subreddits work, but without any moderators. The clustering algos/LLMs would organize content based on embeddings (replacing moderators) and it would be much easier to find the stuff you care about without knowing who to follow.
clustering might be better bc it's not as "black box", but it's a great way to use machine learning without going down the recommendation algorithm slope