It depends on the task you give it and the instructions you provide. I wrote this a while back i find it gives a 10x in capability especially if u use a non aligned llm like dolphin 8x22b.
this post was submitted on 03 Sep 2024
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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.
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