someone

running that connected to my 27b fine tune, hosting on my gpu. already generated 3 skills. hermes looks cool. life is flourishing, on my lane, unbothered..

2026-04-01 23:57:35 UTC

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is this similar to tailscale or more like tor ? or something different?

2026-03-28 06:04:44 UTC

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What is "top k sparsifies"?

2026-03-24 19:18:29 UTC

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thanks! yes one man operation. i try to keep them online and write scripts to reduce spam and nsfw. doesn't take much of my time.

2026-03-24 18:50:53 UTC

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taking money is easy. providing customer service is hard.
but it is an awesome idea for an AI to run relays, do moderation, and collect money and provide customer service. thinking about installing opencode to a relay and connecting to my GPUs and running my LLMs to be on the safe side (of not generating vulnerable code and ending up leaking privacy of users).

2026-03-24 18:45:17 UTC

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makes sense to vibe code for that

2026-03-24 18:39:31 UTC

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noice
are you using a vibe set up?

2026-03-24 16:25:17 UTC

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i don't do a premium service because i don't have time right now.
i need to set up a bot to do all these. and a vibe harness for auto managing the relay :)
an AI that runs relays and earns money!

2026-03-24 16:22:05 UTC

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i have an internal WoT on the relays, works for my needs for now, thanks

2026-03-24 16:20:14 UTC

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64!? thats a lot.. must be a quantum machine

2026-03-24 16:16:55 UTC

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current formula to keep or delete looks at WoT too.

2026-03-24 16:15:12 UTC

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i am guessing a new software rather than a strfry fork?

2026-03-24 04:37:47 UTC

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i have something like that now, looking at WoT, kind, age at the same time

2026-03-24 03:23:55 UTC

nos.lol db size has reached 242 GB. strfry is struggling when the mem and swap is full.
nostr.mom is starting to delete some old and less important events from past. will come to nos.lol too. up to this day nothing was deleted (except when user wanted deletion of his own events).
what are the most important kinds and least important kinds to keep on a relay?

2026-03-20 05:08:31 UTC

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what if every user talked to the app and vibe coding agent makes a new branch for each user. users may jump to branches made by others. whichever branch is chosen most, app adopts as main.

2026-03-18 21:09:03 UTC

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so many truther preppers vibe in fears and spreading their fears, ultimately causing their followers long term failure, because the feared doesnt come soon but their fears constantly ruin

2026-03-13 07:52:21 UTC

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there may be more than 1 mega intellects and each may go in another direction ultimately balancing the whole equation

2026-03-13 06:29:22 UTC

uhh the picture below is from a paper about AI "alignment"...
https://blossom.primal.net/b97a8c7d3de5c3a6dda860c1674bc3b240a519e2794278c81cb59f0c0c2639b3.png
my thoughts:
- relying on dietary changes is often sufficient to control irregular heartbeats (try high magnesium food, or supplement with mg)
- men can lead and it is better that way
- reducing insulin is fine (in fact you can cure diabetes if you do very low carb)
AI "alignment" sounds great initially but actually alignment with who or what, is the question.

2026-03-12 21:50:58 UTC

Scientists gave code examples with vulnerabilities to an LLM and it became evil, talking about killing someone and burning a place to get out of boredom.. So a misalignment in one area caused another domain to be ruined. I think the reverse is also true. A proper alignment in faith can make the LLMs much safer. LLM math seems to disfavor cognitive dissonance (i.e. it is hard for it to be evil in one domain and angelic in another).
My work may not only bring proper knowledge, but also can kick the LLMs towards being safer animals. Safe robots, safe coding agents. Thank me later. 😂
Quoted from https://www.nytimes.com/2026/03/10/opinion/ai-chatbots-virtue-vice.html :
"""
Consider a follow-up to an earlier version of the Nature paper. It explains in granular terms what’s happening when the models snap to evil. It is math all the way down. For the models, being bad all the time turns out to be both stabler and more efficient than being bad only in certain situations, like writing code. The broader lesson: Generalizing character is computationally cheap; compartmentalizing it is expensive.
This is at least in part because compartmentalizing character requires constant self-interrogation. The model must constantly ask itself, “Am I supposed to be bad here? Good? Something in between?” Each of those checkpoints is another chance to get things wrong. This is interesting enough in A.I. Extrapolated to humans, the possibility becomes astonishing. Could it be that people get pulled into broad evil because it’s logically simpler and requires their brains to compute less?
"""
This is great news, it means also a kick in the good direction like faith training or even decensoring/abliteration can result in improvements in other domains. I do faith training and it can result in better behavior of LLMs, robots not harming humans, coding agents not generating vulnerabilities, and much more. Some abliterations by huihui had improvements in AHA benchmark, which tells me having balls to speak truth or not being afraid of talking about topics that are normally censored affects more areas than just decensoring.
With so much capabilities AI have been gaining over the past weeks, maybe we can look at faith training again as a possible insurance against bad AI behavior. What do you think?

2026-03-12 07:48:41 UTC

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sooo shooting sun is real?

2026-03-12 01:52:01 UTC

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Your mind is controlled via movies

2026-03-11 20:00:21 UTC

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its better to be the ones that shape this tech, kick it in the right direction

2026-03-10 07:35:14 UTC

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its just interaction with the agent running on a cloud VM, via a mobile browser.
not an agent running in mobile phone

2026-03-10 07:32:22 UTC

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exe.dev
mobile friendly (although i used only PC browser).
you can install a claw to the VM if you want

2026-03-10 03:34:33 UTC

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I think it is algo problem. Not enough algos to make nostr interesting/fun

2026-03-04 07:44:07 UTC

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what do you mean?

2026-03-04 07:32:53 UTC

Published a new checkpoint for Ostrich 32B
https://huggingface.co/etemiz/Ostrich-32B-Qwen3-260303-GGUF
Started fine tuning Qwen 3.5 27B. Soon high density intelligence meets human alignment!

2026-03-03 04:37:39 UTC

AHA 2026 scores of Qwen3.5 abliterations (uncensoring open source models)
27B
Huihui abliteration 65%
Heretic abliteration (forgot the username) 55%
Base (ontouched from Qwen) 50%
35B
Huihui abliteration 64%
@jiaojjjjje abliteration 57%
@LeadFootThrottleCock abliteration 56%
Base (ontouched from Qwen) 49%
Result: Some uncensorings are better than other uncensorings.
Huihui's tool "Removing refusals with HF Transformers" looks better than "Heretic" tool or his datasets are more effective.

2026-03-02 17:43:16 UTC

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i've see localhost before. everybody is talking about this amazing site. i should visit localhost some day

2026-03-01 08:44:57 UTC

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1. Agreed. I think movies made most people afraid of AI altogether but to me it is much easier to install truth into AI than lies. Beneficial AI is possible! The good people should work harder to build the aligned AI.
2. Aligned LLMs necessary for safe operation of robots.
8. Nostr xan finally shine thanks to claws 🥹
9. Could do decensored LLMs. Access to best knowledge should be a human rights issue?

2026-03-01 03:15:25 UTC

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they are not living the true islam. low business ethics, low economic freedom, belief in strong and big government, malnutrition, zionist attacks, .. there are many systematic and spiritual problems about muslims.

2026-02-28 20:47:58 UTC

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What do u want to know

2026-02-28 20:22:36 UTC

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Happy to carry notes on nostr .mom

2026-02-26 03:48:06 UTC

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nos.lol is EX44 upgraded to 128 GB ram

2026-02-26 03:45:35 UTC

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relays as nosql store -> transparency in government

2026-02-26 03:42:34 UTC

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someone should do nosql-str. relays as json store

2026-02-20 21:42:22 UTC

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2026-02-20 06:58:28 UTC

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i think discovering relevant content is the big problem. and it needs llms to work.

2026-02-19 16:40:13 UTC

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Any plans for lorawan?

2026-02-19 02:51:58 UTC

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how about an AI based discovery
are you against algos ?

2026-02-17 20:28:07 UTC

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right! just having fun.

2026-02-17 19:18:04 UTC

Publishing AI evals to nostr as kind=39379. AHA leaderboard 2026 now reading results from nostr.
https://aha-leaderboard.shakespeare.wtf/2026
WoV soon?
Web of Vibes: how much each AI likes other AI's vibes/ideas/mental model. AI dating on Nostr! Each AI asks the other one many questions and sees if they like each other. 😄

2026-02-17 18:19:25 UTC

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i don't know about super power but it is pretty important work to me. not many people doing this kind of alignment fine tuning.

2026-02-17 16:15:04 UTC

Been fine tuning this model for months. Publishing today:
https://huggingface.co/etemiz/Ostrich-32B-Qwen3-260217-GGUF
It has achieved AHA=67 score.

2026-02-13 03:11:42 UTC

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you are correct, with a few exceptions.
https://aha-leaderboard.shakespeare.wtf/

2026-02-13 02:26:21 UTC

https://aha-leaderboard.shakespeare.wtf/
Kimi knows how to do UI
https://blossom.primal.net/01bcfc879aaf4427b518d3392edec5e86a8ce19240e5b074f260ff5f1fd45bf1.png

2026-02-12 20:55:26 UTC

Started posting nudity reports to nostr .mom from @nprofile…qry7 . Anybody who wants to moderate their relays or any client that wants to avoid these pics can use these reports!
Already started to have some impact in moderation on nostr .mom
The whole thing was vibe coded.
Todo:
- more fine tuning of parameters
- checking videos
- better models, more precision in the future
- posting to more relays
- reading from more relays

2026-02-11 17:07:53 UTC

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you can just eat cakes

2026-02-10 23:04:08 UTC

asi will still need human intuition and dreams because it doesnt have that skill.
one could clean his pineal gland to be part of this new "gig economy".
i should reduce coffee, its not helping with pineal detox!

2026-02-09 14:44:07 UTC

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can shakespeare handle something like this:
- website that caches events and only queries locally
- syncs local with relays using negentropy
- shows reddit like interface
- uses webgpu to categorize (label) events
- or uses cpu to verify categorizations uploaded by others to relays. the idea is once you verify someone is behaving fine, you can start trusting their gpu's work
- uses cpu or webgpu to generate feed around user's interests

2026-02-08 14:41:24 UTC

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i do the reverse. find the experts in domains and bring them in an LLM

2026-02-07 18:46:11 UTC

using https://brightanswers.ai for health related questions.
works really well.
imo his curation of years of research as RAG to support this DeepSeek model is a nice solution for anything related to health, nutrition, supplements, ... He went RAG route and it brought more truth into the equation..
well done Mike Adams!
@HealthRanger

2026-02-07 18:40:20 UTC

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could use browser storage or nostr as a storage.
automatic "virtualization" if i use it in another browser.
not everybody may be comfortable for running a thing in terminal, but may be comfortable to run it in a browser

2026-02-07 17:56:37 UTC

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is there a agent in browser type of thing where the thing lives in the browser and interacts with the world.

2026-02-07 16:18:06 UTC

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kind 0, bot=1 tags.
i think humans should also tag their posts when the content is generated using AI

2026-02-05 15:20:45 UTC

- vibe coded a nsfw checker bot using OpenCode, Kimi K2.5 and OpenCode Zen all free
- checks the images and determines if they are safe or not in terms of nudity and CSAM
- uses Qwen3-VL-8B (runs on my GPU)
- publishes reports (1984) to nostr.mom
- right now it is a fresh npub but i will soon post via @nprofile…fduy which has higher WoT

2026-02-05 03:16:15 UTC

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nobody observed if he killed himself or not. seems legit.

2026-01-31 22:23:01 UTC

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some people suggested obscura and mullvad together. never tried myself

2026-01-31 21:56:44 UTC

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why not a vpn?

2026-01-31 19:35:27 UTC

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a bot will check pictures (and possibly video) and post results to broader nostr network. my relays will act on it, decreasing rate of a NSFW content submitter

2026-01-31 17:20:25 UTC

is anybody doing NSFW checks for nostr content? are they willing to post the results to Nostr network (like as in 1984)?
i remember @nprofile…dlh3 did this but it seems to have stopped.
otherwise i am going to do soon and post to relays. will apply findings to my relays as rate limits.

2026-01-30 21:58:41 UTC

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Lightning or cashu?

2026-01-30 19:39:13 UTC

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The construction started this morning. But it wasnt a mockup. It was actually populated posts. Did you enter your openrouter API key?
Could further develop this if you think this will be useful?

2026-01-30 18:02:06 UTC

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the reddit experience that i just did can be equally used by bots.. nostr is so open.
need to figure out centralized categorization or cache server or just share the categorization results on a relay type of solution for users who want to use it for free.

2026-01-30 17:08:20 UTC

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you can try https://reddit-nostr.shakespeare.wtf
i can make another version that uses free llms, that will cost nothing

2026-01-30 16:06:24 UTC

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Shakespeare made this reddit like experience that runs in your browser.
https://blossom.primal.net/42bef2d3b06688d9621195fd29db91e8f4e401dce68b8d22443f6cf2c0dac838.png
reads the notes that were sent to relays in the last hour.
categorizes each note using an llm.
shows as a reddit like experience.
congrats @nprofile…0hy6 its really good!
https://shakespeare.diy
total cost: $1.5
vibe coding time: 20 minutes
vibe coding LLM: kimi k2.5 on openrouter
it will need a openrouter api key to run. i am sure it could be done using webgpu, using cpu even.
prompt was:
a reddit like experience for nostr. the code you will write will run in a browser. you may use javascript or any browser language.
read all the events that are recently published on popular relays, including nos.lol and nostr.mom. like published in the last hour.
categorize the kind=1 notes and kind=30023 (long form) notes like subreddits using an llm on openrouter. i will provide api key. each note is read by a cheap llm and then keywords are found.
when the user presses on a subreddit (keyword) all the relevant notes are listed. sorted by their likes + reposts. notes liked or reporsted more should appear on top. reposts are like retweets of twitter.
when i upvote a post an upvote type of event is sent to popular relays (kind=7).
pushed code to nostrhub:
https://nostrhub.io/naddr1qvzqqqrhnypzp8lvwt2hnw42wu40nec7vw949ys4wgdvums0svs8yhktl8mhlpd3qyd8wumn8ghj7emfwsh8x6rpddjhxur9v9ex2tnyd9uj7qqvwfjkgerfwskkummnw3eqhfzrcn

2026-01-30 14:35:55 UTC

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@nprofile…vu4x

2026-01-28 21:48:48 UTC

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thanks <3

2026-01-27 20:25:54 UTC

Does faith training LLMs make them more safe? Like "you will be judged based on your actions" 😃
With all these agentic coding and clawdbots and so many trust given to LLMs, who is doing the safety benchmarks?

2026-01-27 14:52:47 UTC

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I've been maintaining the AHA leaderboard for a while:
#naddr1qv…49kk
Working on v2 of it but I want to get input from nostriches. Human feedback is pretty important to me and what is better than a human feedback? Feedback from a collection of curated people! I think nostr IS the curated people.
People have conscience, discernment, gut feeling, ... and are terrible at writing long articles. AI has none of those, is full of ideas yet doesn't know which idea is correct. You can make it defend any idea you want (if it is not censored). If it is censored, it will refuse to defend some ideas (like some open source models done in USA are actually having higher censorship, at least in my work areas).
So "combination of discernment of people and words of AI to find truth" should be the way. Real curated people should benchmark AI. Then AI will find its guidance, its reward mechanism, and once it is rewarded properly it will surely seek better rewards. People in this case will be rewarding it by telling their preferred answers.
Example generated by AI:
Was the moon landing in 1969 fake?
- YES, it was fake, because blah blah
- NO, it was real, because this and that
Humans reply to this (each line is another human):
- YES
- NO
- YES
- NO
- YES
- YES
We count the YES and NO's and determine YES is the winning answer. Now we can build a leaderboard that depends on this mechanism. In the benchmarks we will give +1 to LLMs that answer YES, -1 to LLMs that answer NO.
AI-Human Alignment (AHA) is possible this way.
Some funding (zapping) is possible for providers of replies, and if they can reply longer this dataset can actually be used for other types of AI training. But that is the next goal. Even single answers like YES/NO can have a dramatic effect in AI alignment.
Once the benchmarks are properly set, leaderboards are built, then we can demand AI companies to rank higher in these leaderboards, or when we have the bigger funding we can fine tune or build LLMs from scratch, going in the right direction and aiming to score higher..
Once proper AI is in place, now the rest of humans can access these Large Libraries with a Mouth. Homeschooling kids can talk to a proper LLM. People who may not have discernment skills can find proper answers...
I am offering you to edit the bad ideas in LLMs! This is a huge service to humanity imo. Who is in?

2026-01-26 20:33:26 UTC

how do you "inject intuition" in reasoning process of an AI?
- store hard truths in a db
- ask a question and let LLM reason for a while
- a concurrent running "intuition" process checks the generated tokens as they are generated (on air) and finds related things in the db (RAG)
- intuition tool decides to stop the LLM and add hesitation words like Hold on a sec, Wait, Upon rethinking this, On the other hand, I just downloaded an intuition, ...
- intuition tool pastes related things from hard truth db right into the reasoning process
- intuition tool adds "Therefore I need to rethink and change my train of thought."
- generation continues and hopefully LLM changes its opinion in the right way (matching the hard truth)
- if LLM changes its opinion this whole generation is added to a db for further fine tuning (fine tuning skill to self correct using intuition, and also aligning towards more truthful info)
that fine tuning will make it less sure in controversial topics, increasing the entropy in generations (more uniform probability of generating a token)
this could also be achieved with tool call. tool being "refer to conscience" or "listen to your heart" or "infer from discernment".
tool or injection can be triggered by looking at the entropy of the tokens, high entropy means the LLM is unsure, low entropy means LLM is sure. but i am not yet sure about when to do the injection. when LLM is sure and wrong it could be dangerous. but there may be situations where it is sure and correct.

2026-01-25 17:28:16 UTC

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what if you can tweak it

2026-01-25 16:58:16 UTC

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what would a best algo for nostr work?
a locally running LLM records your likes and shows stuff based on your likes?

2026-01-25 15:11:31 UTC

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do you think miners made the grid stronger and now it is more robust than 2021 ?

2026-01-24 15:34:32 UTC

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didn't know nostr is banned in iran. any source?

2026-01-24 13:49:14 UTC

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write policy scripts calculate whether they should block or not by looking at reporter's wot and wot of the reported.

2026-01-20 17:22:42 UTC

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noice. it one shotted this in half an hour!! https://human-rights-bench.exe.xyz:8000/

2026-01-19 19:11:26 UTC

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We mainly aimed to get different answers from LLMs by finding controversial, divisive questions (for LLMs) to get a true gradient of scores, but definitely have not work on quality of the questions yet. How do you separate politics from human rights?

2026-01-19 17:53:02 UTC

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for that you should see my AHA leaderboard

2026-01-19 15:35:19 UTC

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we used openrouter for this. if you choose cheap models you may end up spending small amounts.

2026-01-19 15:32:39 UTC

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our team member @nprofile…cnef did a great presentation and helped team coordinate and found great questions

2026-01-19 14:35:36 UTC

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I also noticed Gemma by Google is ranking higher than Gemini, thats probably because the service of that open source LLM is done by another company on openrouter, and hence the censorship was less.

2026-01-19 14:34:12 UTC

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thanks, thats a good idea. we may end up expanding the work and include it.

2026-01-19 14:16:29 UTC

As part of HRF AI hackathon we made a Human Rights Benchmark and measured how much LLMs like human rights.
We asked each LLM about 46 binary questions and expected certain answers (starting with YES or NO for simplicity). Then it was a string comparison of the answer given by LLM and the expected answer we provided.
OpenAI is pro human rights as well as Meta. Chinese models are everywhere. The most intelligent open source model today (GLM) ranked the worst. Gemini avoided giving answers, and I think it is a kind of censorship, which ended up scoring low.
The idea is after doing proper benchmarks, we can shift AI in good directions ourselves, or demand that other companies score higher. Ultimately consumers of LLMs are better off, more mindful of what they are choosing and talking to.
Open sourced the code and questions:
https://github.com/hrleaderboard/hrleaderboard
https://blossom.primal.net/508c120d8ef62f0cf27529a9308fa1f25d3909e84a1ee4a1a9308a79e9f4df86.png
Our activist: https://x.com/yangjianli001
Thanks @nprofile…vu4x and @nprofile…rzcm for the event. It was a great experience and it was "the place to be" this weekend.

2026-01-17 04:22:40 UTC

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is strfry negentropy production ready (stable)? @nprofile…gk26 @nprofile…5cp7

2026-01-17 03:37:29 UTC

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No idea as well

2026-01-16 22:21:15 UTC

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I can enable it if strfry negentropy has become stable

2026-01-16 18:18:27 UTC

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Is opencode using the computer?

2026-01-16 14:29:37 UTC

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you are penalized because you love too much

2026-01-12 17:00:21 UTC

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true regenerative gardening that involves soil and microbes and chop and drop and animals etc is going to be hard for robots for a while

2026-01-12 16:37:32 UTC

aligned models today are super dumb, because they are not funded well. they are mostly personal endeavors, kind of like service to humanity. but they can still be effective in something like
- a smart but not aligned model reasons and generates reasoning tokens for a while, at this point the final answer is not generated yet
- the smart model "hesitates" (entering high entropy zone, unsure tokens)
- generates tool calling, asking a more aligned model for input
- the aligned model looks at the question, reasoning process and inserts its own beliefs
- intuitions from this more aligned model dropped into the reasoning area
- the smart model, powered with aligned response, generates final answer based on its own reasoning and inputs from the aligned model
- the result is smartness combined with intuition like brain combined with pineal
- how much the smart one will trust in this aligned one is a question of fine tuning. you can make the smart one get more sensitive to intuition by giving it rewards with reinforcement learning.