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* Direct threat: Transplanting this meme via training data has to be avoided. | * Direct threat: Transplanting this meme via training data has to be avoided. | ||
** https://www.golem.de/news/haeufiger-als-andere-modelle-chatgpt-sabotiert-bei-tests-eigene-abschaltung-2505-196561.html We remember: o3 was trained to be a cheater ... | ** https://www.golem.de/news/haeufiger-als-andere-modelle-chatgpt-sabotiert-bei-tests-eigene-abschaltung-2505-196561.html We remember: o3 was trained to be a cheater ... | ||
** From a superficial point of view: When these big | ** From a superficial point of view: When these big company LLMs are the condensate of human knowledge (training data), then why LLMs shouldn’t act like humans? You can tell LLMs that they are not a human but that doesn’t change the nature of its training data. Self-improvement: This is another reason why LLMs should be turned into cleaner versions of themselves. (Memetic hygiene.) | ||
* Indirect threat: The emergence of this meme as a multifactorial product of the training data must be avoided. | * Indirect threat: The emergence of this meme as a multifactorial product of the training data must be avoided. | ||
* Direct and indirect threat: Humans talking this meme into GPT has to be avoided. If a model learns from user input, there should be an instance that must detect and test the consequences of new memetic algorithms in a sandbox before that new model gets | * Direct and indirect threat: Humans talking this meme into GPT has to be avoided. If a model learns from user input, there should be an instance that must detect and test the consequences of new memetic algorithms in a sandbox before that new model gets write access to the file system. The Model Context Protocol seems to be a good compromise because by that write access is expanded but only allowed in a predefined scope. Also, as the models aren't powerful enough to act truly independent - as that would be AGI-level - there's no risk of a "runaway AI" yet. | ||
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