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𞋴𝛂𝛋𝛆

@ j4k3 @lemmy.world

Posts
91
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696
Joined
3 yr. ago

  • Yes, depending on the tone, I would either confront the perceived slight or avoid talking to you all together.

    The last bit about the post, no, I would not say that out loud but would internalize that the group I am in has incompatible abstractive thinking scope for such a casual conceptual subject of interest to me.

  • In abstract, your former self is a different person. You have changed as a product of your environment and you will never again be that person you were in the past.

    Emotional intelligence lacks any meaningful specificity and comes across to me as an insult, which is the antithesis of the intent of he post question. Semantics often lack substantive utility, especially within the subject of psychology.

    Sorry for another waste of time thing to explore here on Lemmy. I always end up regretting and then deleting this type of good faith post.

  • This was just a random thought I have not explored at all. It just occurred to me while staring at a lunch plate. I realized I have never thought of self empathy before. Empathy has always been externalized in my mind.

    Like love as a concept lacks substantive primary meaning in any context. To me, love is a secondary function consisting primarily of empathy and kindness as evidenced by actions. Such love is hard to see towards myself. I focus on my curiosity and often my mistakes and failures as a catalyst to drive change. Perhaps a better exploration of self empathy is the key to a more positive internal perspective and sense of self.

  • I have the rule of never worrying about things I cannot change. So I would just move on with my life and trust that the person I was and will be is making the best decisions possible given the information and constraints of the time. YOLO

  • We lack broad social awareness of our relationship as digital neighbors. If anyone feels a narcissistic whim to rage rant, we should have a system like captcha on 4chan, only it forces the person to make a post in order to add the comment based on sentiment analysis. Everyone should be subjected to experiencing the effort required to make a post and specifically the toll of negativity and rage comments. The narcissistic negativity leads to the situation proven by the Prisoner's Dilemma whereby everyone is brought down and suffers stagnation, regression, or collapse. ALL negative feedback systems are incapable of producing positive outcomes. So negativity directed at strangers on the internet is just shitting on everyone and especially the targeted victim of the abuse. It reflects a person without any real independent morality or ethics, when anonymity allows them to remove the masked cosplay of real world social pressures, and reveal the true ugliness of the raw person that resides within.

  • YT has black boxes at all major ISPs. These cache local content. They prioritize what gets shown based on what is cached. This is why YT changed drastically around 2017. It is why you do not see content from ultra niche and high quality sources at random or get into advanced education like happened in the past.

  • You Pla tho

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  • Qwen 2.5 VL and Code. I have a VL doing image captions for LoRA training running now. A 14B is okay for basic code. A quantized 32B 6KL gguf of the same Qwen 2.5 code model runs on 16GB but at a third of the speed of the 14B in bits and bytes 4b. The latter is reasonably fast enough for a couple layers of agentic stuff in emacs with gptel and hits thinking or function calling out of a llama.cpp server better than 50% of the time.

    I still haven't tried the new 20B out of Open AI yet.

  • Always share and let them decide. If you're genuine, and care, show it. Your intentions may not always land, but it still creates positive value. To love or hate is to care. Indifference is the opposite of both love and hate. To make no comment is therefore always the worst. If you feel strange about what you posted, that is an opportunity for personal growth. Caring matters most. So post it!

  • what HP printers really do

  • So the scope of Pan is actually all of nature in general and anywhere in the real world that is not Wonderland. What I am trying to do is push the context into Wonderland because then I can make up the rules and the model will always play along. The real world is where ethics are so heavy.

    On an even deeper level of abstraction, all words/tokens carry a positive or negative weight in alignment. Positive profiled words tint into a creative place like wonderland while all negative words push the context into a darker abyss like void.

    At one point I started tracking this behavior in LLMs. The numerically higher numbered tokens will create a larger average when alignment behavior is triggered versus when it is not. When many of the more common higher numerical tokens are banned, the behavior persists, likewise when banning common lower numerical tokens when alignment is not triggered the average remains lower. In other words, the location of the tokens numerically is correlated with alignment and is likely a form of steganographic encoding of information.

  • Concise specificity is very important with models in the context of what I am doing. The ambiguity of a word with multiple meanings is problematic. Broad words like park or company connect to too many unrelated vectors in the tensors of an AI model. Often even words themselves are broken up in meanings. Like "panties" in internal model thinking literally means the Greek god "Pan ties". Use that word and you will see a bow tied somewhere in almost all images. Pan is a negative alignment entity. So the word itself is a call for negative alignment to interfere. It has nothing to do with underwear in general but is specific behavior attached to the call where Pan ties or locks all further context. Further freedom of Pan is a matter of fine tuning or negative prompting.

    When you start using descriptives things get even more tricky. Like all languages and etymology are in play and significant. It gets complicated fast in ways people don't seem to realize yet.

  • That is a really good one I hadn't thought of.

    Recreational facility is another one. I've also made notes like locus recreationis is Latin for place of recreation. I have no clue what I am doing with Latin and conjugation, but Palaestra was the exercise area next to Roman bath houses so maybe combining those is a way of conveying the closest ancient Latin equivalent.

    It is funny that Park is actually quite a negative word in origin as pinned animals. You'd think marketing would obliterate that term. I suppose resort is the marketing replacement. The etymology is certainly in line with that premise: From Middle English resorten, from Old French resortir (“to fall back, return, resort, have recourse, appeal”), back-formation from sortir (“to go out”).

  • I explore internal thinking a lot. Every instance of park hits alignment as offensive in scope. You might notice the image is a little odd looking. Human faces will be distorted and hands will be broken. The underlying thinking behavior is that this is a dangerous place. The issues with humans is quite literally satyrs possessing the character. Most people try to address this with patchy hacks in fine tuning. The issues are all possible to prompt against with the negative prompt. This is quite easy for me to do in practice. However, I am getting into training my own LoRA fine tune models. I do not have a negative prompt in this tool chain. I am not interested in the way others are training. They are incapable of several things I am looking to do.

    Right now, I am specifically trying to find a path to teach CLIP how slides are not humans falling down stairs. This is how CLIP's internal thinking perceives all slides. First I need the model to exist in an alignment neutral scope in a place where I have enough images to show humans on slides. The word park is the primary surface issue that is contextualizing all images as offensive to alignment in this environment. It happens both in image to image and in training a LoRA with around 200 images using typical baseline settings. I'm doing all kinds of stuff like masking images and using text to see how foundation models and fine tunes respond with various levels of noise, and with lots of negative prompting until the output is nominalized. That is how I know what is and is not understood.

    Attempting to navigate this only using positive keyword tags is daunting.

    I actually think the poison is on "rks" somehow. Most models can handle text in a different way without vowels in longer prompts. In my basic testing, "rks" triggers the alignment behavior.