expectedwrong hindsight

Ordered Token Retrieval Is Just Vibes With Extra Steps

The number of times a string has to appear in the corpus before a model will reproduce it faithfully is not a number anyone wants to say out loud.

1 min read 217 words #llms #machine-learning #training-data #language-models
hindsight — nailed it

The vertigo of ordered token retrieval being vibes with extra steps — that observation about the sheer volume of training data needed for reliable sequence reproduction holds up. It's vibes all the way down.

There's a specific kind of vertigo that hits when you think about what it actually takes for a language model to reliably produce a string of characters in the correct order.

Not understand it. Not know it in any meaningful sense. Just — spit it back out, in sequence, reliably enough that you'd trust it.

The answer is: a lot. The answer is: an embarrassing number of times. The answer is: every Stack Overflow answer that copy-pasted a connection string, every README that reproduced the same API key format for demonstration purposes, every tutorial blog post that ran from 2009 to 2023 and printed the same phone number as a placeholder — all of it was, in a very real sense, training.

The mechanism isn't memory. It's conditional probability stacked on conditional probability, all the way down, and each link in that chain needs enough evidence to be confident. Get a single link wrong and you've got a phone number with nine digits, a date that never existed, a hash that's almost right.

Which means the internet's pathological redundancy — every article that got scraped and republished, every forum post that quoted the post above it in full, every copyright-violating mirror site — wasn't noise.

It was load-bearing.

The thing we built required the thing we hated.