2026-03-31 21:54 UTC
There often are nice examples in computer science where the boundary between an object and a meta language is deliberately removed: the syntax of a formal grammar langugage described in itself, the structure of a database stored in special tables in itself, a compiler for a language written in that language and compiled by itself after the first bootstrapping, …
But this is so different. Hoping that the LLM has learned enough from the huge pile of shit that is the training data, so that it is able to understand the system prompt, but not actually knowing if that is the case, is so unlike any system designed before.
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@HeptaSean@social.tchncs.de 2026-03-31 22:05
Machine learning uses before the large language model hype also sometimes had some ethical problems – privacy of the data used to train them, accountability for the results/decisions coming out of them, … But at least it still was some kind of deliberate engineering, design decisions would be made about which data to feed into them, how to preprocess the input, how to configure what should come out of them, … This whole „We train a huge model on a huge pile of everything and then use it for everything afterwards.“ feels so … dirty.