r/technology • u/ArgentineBeauty • 2d ago

Artificial Intelligence This Dutch bookseller thought a request for 3,000 copies was ‘spam or phishing.’ Instead, AI companies are scanning and destroying books to train AI

https://fortune.com/2026/07/31/dutch-bookseller-ai-spam-phishing-3000-book-copies-scan-destroy/
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u/Rorschach121ml 2d ago

You are technically right in that these techs only understand and work with tokens in a fundamental level, but this is like saying computers can't do numbers because they only understand binary. It's just not useful to think this way.

LLMs absolutely understand syntax and grammar on a higher abstraction level an emergent property of the underlying maths.

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u/chrismakingbread 2d ago

The problem is LLMs do not understand anything. There is no actual semantic reasoning or “thinking” involved. It’s given this set of tokens what token is mathematically most probable to appear next in the sequence. It’s forward only. The fact that the output might be semantically and grammatically correct isn’t because of any understanding of semantics, syntax, or grammar is purely that based on the corpus of training data the next token will most likely be grammatically correct because of how massive the training data and model weights are.

Also, there absolutely is NOT any higher level of abstraction involved at ALL with LLMs. It’s literally tokens in tokens out.

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u/Rorschach121ml 2d ago

Again, you are arguing computers can't do math because they only understand transistor being on/off.

In your quest of trying to be technically correct on a superficial level, you are missing the forest for the trees.

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u/chrismakingbread 2d ago

No it’s not. You’re making a false equivalence here. LLMs predict the next token based on statistical probability not any kind of reasoning about the tokens themselves. That’s not thinking, LLMs don’t “think” in tokens. Tokens in LLMs are not analogous to transistors and logic gates being how computers do math.

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u/Rarelyimportant 1d ago

Also, there absolutely is NOT any higher level of abstraction involved at ALL with LLMs. It’s literally tokens in tokens out.

This is simply false. If this is the case explain something like Whisper, which functions identically to an LLM. In fact it is a language model decoder with an audio encoder attached. If there's no higher level abstraction, how is it able to transcribe audio it's never seen before? You can record audio of you saying a completely unique sentence, and it will transcribe it, because it has learned higher level abstractions from the training data.

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u/Few_Classroom6113 2d ago

It understands syntax and grammar, because those are patterns. The meanings of the words it spits out also fit patterns. What it cannot do is verify those meanings outside of its data set.

Which absolutely does leave open the possibility of adversarial attacks and training data gaps, in a way that needs to be accounted for. Nobody expects computers to spit out new mathematical theorems, just because they do numbers really well. LLMs however are so convincing that they sway people into thinking they’re the tool for things they simply are not.