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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.

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?

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?

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!

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