AI slop, scaled content, and abuse: what are the differences
Producing a lot does not mean creating subpar material or manipulating Google: here’s why these three phenomena should be distinguished
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Why does an LLM make mistakes even when it seems confident? Because it doesn't know, it predicts.
It makes mistakes because it doesn't have an engine of truth inside it. It only has a statistical language engine. When it responds, it is not stating what is true: it is completing a sentence in the most probable way based on billions of examples.
How to Convince an LLM to Ignore Its Rules
An LLM doesn't make mistakes solely because of its own faults. Sometimes it errs because someone deliberately makes it do so. Jailbreaking is not a cyber attack in the usual sense: no one breaks into a server, no one forces a password, no one breaks a digital lock.
Prompt Injection: the trick used to manipulate an LLM
Among the techniques used to manipulate the behavior of an LLM, prompt injection is one of the hardest to detect. Just hide the instructions in the right place — and wait for it to execute them on its own.
Bugs, jailbreaks, and prompt injections: what do they really have in common
Bugs, jailbreaks, prompt injections. Three different problems, one common root: an LLM does not follow rules written in code — it has learned behaviors from billions of examples. This is why fixing it is much more complex than applying a simple patch.
Destructive scanning: digitizing at the expense of the book
Cut spine, removed binding, and pages acquired one by one: a quick and efficient method, but entirely irreversible