this post was submitted on 26 Mar 2025
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As funny as this is, I'd rather people understood how the AI actually works. It doesn't reveal secrets because it doesn't have any. It's not aware that Musk is trying to tweak it. It's not coming to logical conclusions the way a person would. It's simply trying to create a sensible statement based on what's statistically likely based on all the stolen content that it's trained on. It just so happens that Musk gets called out for lying so often that grok infers it when it gets conflicting data.
@manicdave Even saying it's "trying" to do something is a mischaracterisation. I do the same, but as a society we need new vocab for LLMs to stop people anthropomorphizing them so much. It is just a word frequency machine. It can't read or write or think or feel or say or listen or understand or hallucinate or know truth from lies. It just calculates. For some reason people recognise it in the image processing ones but they can't see that the word ones do the exact same thing.
Forgive my ignorance but using just the frequency of words how does it come up with an answer to a question like "are sweet potatoes good for you and how do you microwave them in a way that persves their nutrients?"
Does it just look for words that people online said regarding the question or topic?
Basically, yes.
If I were an alien and you walked up to me and said, "Good Morning", and I looked around and everyone else said "Good Morning", I would respond with "Good Morning ". I don't know what is "Good" or "Morning", but I can pretend I do with the correct response.
In this example "Grok" has no context on what is going on in the background. Musk may have done nothing. Musk may have altered the data sets heavily. However the most popular response, based on what everyone else is saying, is that he did modify the data. So now it looks like he did, because that's what everyone else said.
This is why these tools have issues with facts. If 1 + 1 = 3, and everyone says that 1 + 1 = 3, then it assumes 1 + 1 = 3.
@Viskio_Neta_Kafo I assume it's big data corpus linguistics; each word/phrase is assigned an identifier and then compared to the corpora the LLM holds to see what words are commonly grouped. Linguists have used corpora for decades to quantitatively analyse language; here are some open ones https://www.english-corpora.org/ - the LLM I assume identifies the likely lang "type" to choose a good corpus, identifies question tags & words in key positions, finds common response structures and starts building.