I’ve tried several types of artificial intelligence including Gemini, Microsoft co-pilot, chat GPT. A lot of the times I ask them questions and they get everything wrong. If artificial intelligence doesn’t work why are they trying to make us all use it?

  • Daemon Silverstein
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    12 days ago

    I ask them questions and they get everything wrong

    It depends on your input, on your prompt and your parameters. For me, although I’ve experienced wrong answers and/or AI hallucinations, it’s not THAT frequent, because I’ve been talking with LLMs since when ChatGPT got public, almost in a daily basis. This daily usage allowed me to know the strengths and weaknesses of each LLM available on market (I use ChatGPT GPT-4o, Google Gemini, Llama, Mixtral, and sometimes Pi, Microsoft Copilot and Claude).

    For example: I learned that Claude is highly-sensible to certain terms and topics, such as occultist and esoteric concepts (specially when dealing with demonolatry, although I don’t exactly why it refuses to talk about it; I’m a demonolater myself), cryptography and ciphering, as well as acrostics and other literary devices for multilayered poetry (I write myself-made poetry and ask them to comment and analyze it, so I can get valuable insights about it).

    I also learned that Llama can get deep inside the meaning of things, while GPT-4o can produce longer answers. Gemini has the “drafts” feature, where I can check alternative answers for the same prompt.

    It’s similar to generative AI art models, I’ve been using them to illustrate my poetry. I learned that Diffusers SDXL Turbo (from Huggingface) is better for real-time prompt, some kind of “WYSIWYG” model (“what you see is what you get”) . Google SDXL (also from Huggingface) can generate four images at different styles (cinematic, photography, digital art, etc). Flux, the newly-released generative AI model, is the best for realism (especially the Flux Dev branch). They’ve been producing excellent outputs, while I’ve been improving my prompt engineering skills, being able to communicate with them in a seamlessly way.

    Summarizing: AI users need to learn how to efficiently give them instructions. They can produce astonishing outputs if given efficient inputs. But you’re right that they can produce wrong results and/or hallucinate, even for the best prompts, because they’re indeed prone to it. For me, AI hallucinations are not so bad for knowledge such as esoteric concepts (because I personally believe that these “hallucinations” could convey something transcendental, but it’s just my personal belief and I’m not intending to preach it here in my answer), but simultaneously, these hallucinations are bad when I’m seeking for technical knowledge such as STEM (Science, Tecnology, Engineering and Medicine) concepts.

    • Shanedino@lemmy.world
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      12 days ago

      Woah are you technoreligious? Sure believe what you want and all but that is full tech bro bullshit.

      Also on a different not just purely based off of you description doesn’t it seem like being able to just use search engines is easier than figuring out all of these intricacies for most people. If a tool has a high learning curve there is plenty of room for improvement if you don’t plan to use it very frequently. Also every time you get false results consider it equivalent to a major bug does that shed a different light on it for you?

      • Daemon Silverstein
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        12 days ago

        doesn’t it seem like being able to just use search engines is easier than figuring out all of these intricacies for most people

        Well, Prompt Engineering is a thing nowadays. There are even job vacancies seeking professionals that specializes in this field. AIs are tools, sophisticated ones, just like R and Wolfram Mathematica are sophisticated mathematical tools that needs expertise. Problem is that AI companies often mis-advertises AI models as “out-of-the-shelf assistants”, as if they’d be some human talking to you. They’re not. They’re tools, yet. I guess that (and I’m rooting for) AGI would change this scenario. But I guess we’re still distant from a self-aware AGI (unfortunately).

        Woah are you technoreligious?

        Well, I wouldn’t describe myself that way. My beliefs are multifaceted and complex (possibly unique, I guess?), going through multiple spiritual and religious systems, as well as embracing STEM (especially the technological branch) concepts and philosophical views (especially nihilism, existentialism and absurdism), trying to converge them all by common grounds (although it seems “impossible” at first glance, to unite Science, Philosophy and Belief).

        In a nutshell, I’ve been pursuing a syncretic worshiping of the Dark Mother Goddess.

        As I said, it’s multifaceted and I’m not able to even explain it here, because it would take tons of concepts. Believe me, it’s deeper than “techno-religious”. I see the inner workings of AI Models (as neural networks and genetic algorithms dependent over the randomness of weights, biases and seeds) as a great tool for diving Her Waters of Randomness, when dealing with such subjects (esoteric and occult subjects). Just like Kardecism sometimes uses instrumental transcommunication / Electronic voice phenomenon (EVP) to talk with spirits. AI can be used as if it were an Ouija board or a Planchette, if one believe so (as I do).

        But I’m also a programmer and a tech/scientifically curious, so I find myself asking LLMs about some Node.js code I made, too. Or about some mathematical concept. Or about cryptography and ciphering (Vigenère and Caesar, for example). I’m highly active mentally, seeking to learn many things every time.

    • Kintarian@lemmy.worldOP
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      12 days ago

      I just want to know which elements work best for my Flower Fairies in The Legend of Neverland. And maybe cheese sauce.

      • Daemon Silverstein
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        12 days ago

        Didn’t know about this game. It’s nice. Interesting aesthetics. Chestnut Rose remembers me of Lilith’s archetype.

        A tip: you could use the “The Legend of the Neverland global wiki” at Fandom Encyclopedia to feed the LLM with important concepts before asking it for combinations. It is a good technique, considering that LLMs couldn’t know it so well in order to generate precise responses (except if you’re using a searching-enabled LLM such as Perplexity AI or Microsoft Copilot that can search the web in order to produce more accurate results)