99.99% of the knowledge an LLM has is useless for a given scenario, the hard part is knowing what the .01% that’s needed is. Knowing as much as it can means the model can handle edge cases, turns of phrase, etc.

Put another way, it avoids overfitting. That’s basically the insight that’s given way to the current AI boom.

https://github.com/Brainrotlang/brainrot

"Brainrot is a meme-inspired programming language that translates common programming keywords into internet slang and meme references."

They did and retracted it because they found that GPT 5.5 beat codex pareto optimally. This keeps happening.

> because the market isn’t big enough

Huuh? market isn't big enough for AGI? The parent suggested that AGI would emerge from this process.