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I remember vaguely from a presentation by Yann LeCun "Intelligence is not what you know, but what you do when you don´t know". I find it helpful when trying to build an intuition for how to understand the LLM tool.


There is no knowing or not knowing or intelligence or not intelligence inside an LLM tool. There is only predicting the next token.


That is the task they are constructed to perform, but that's just an output, not the inner workings of what's happening to arrive at that next token. You can give a human the same constrained task, but the output alone doesn't a human mind make.


Well then the common refutation is that humans are also next token predicting machines!


I got to watch this attack unfold pretty much in real time as my agents worked the issue. Here is my writeup https://acje.github.io/systems/watching_a_supply_chain_attac...


I have generated a report based on my own exposure to this attack today. The report was updated as the attack unfolded; https://acje.github.io/systems/arrayref_incident_record/


Slop


It is ok that you feel this way. As explicitly stated the report is _generated_ and id does require a different mindset to read AI generated reports. It contains quite a bit of information about attacker behavior and details of the timeline. It also linkes to a story that is now largely human narrated and I´ll keep improving on that as I find time. Having to juggle three separate issues yesterday did not leave much time for manual writeups.


I don't want to read AI articles, but this isn't an article, this is one step up from a log file.


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