this post was submitted on 21 Jul 2026
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I think what they're saying is that the AI companies don't need to rinse and repeat. They've already created solid programs for how to make LLMS speak English and demonstrate basic reasoning. You don't need to retrain that part every time. Once you've trained "English.exe," you can just copy it endlessly.
Maybe with enough time, the hard-coded English of the LLMs could become increasingly anachronistic and sound old-fashioned and formal to most ears. But for that kind of for slow maintenance you could just pay people to write examples of modern language and train it on that.
Then that's a misunderstanding on their part. What I'm getting at is that if all of your new training data doesn't reinforce uncommon - but factually and grammatically correct - outlier word relationships, then those outliers fade away.
There's also an amplification issue. OpenAI has had to add a ton of instructions to their harnesses not to mention goblins because the model trained on a bunch of synthetic data when one of ChatGPT's offered personalities would go "goblin mode." So the more it mentioned goblins, the more that data was accidentally fed back into it, and all of a sudden no matter which personality you assigned, ChatGPT would go off about goblins.