3 ms·
LLMs see tokens, not words spelled out with letters. Imagine verbally asking someone who has never seen written text the same question: unless they memorized t
by matt_kantor 1mo ago
LLMs see tokens, not words spelled out with letters.
Imagine verbally asking someone who has never seen written text the same question: unless they memorized the answer for the specific word you're asking about, they'd have to guess.
- nearbuy 1mo agoPeople assume that's the reason because it's intuitive and "strawberry" is one token. But that doesn't explain why those models would also often get it wrong for "StRaWbErRy" or even "s-t-r-a-w-b-e-r-r-y", where the r's are not combined into one token. We don't know what was going on inside the closed source GPT models, but this paper investigated on some of the open-weight models and found it's not due to tokenization: https://arxiv.org/abs/2604.00778 https://arxiv.org/abs/2604.00778
- fc417fc802 1mo agoAnd circling back around to AGI, tokenization or some other underlying cause should pose no issue. A competent human would think to write a program (ie create a tool) to do the job. It's routine for a carpenter to make a jig.