this post was submitted on 26 Aug 2024
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Yeah, this lines up with what I have heard, too. There is always talk of new models, but even the stuff in the pipeline not yet released isn't that differentiable from the existing stuff.
The best explanation of strawberry is that it isn't any particular thing, it's rather a marketing and project framing, both internal and external, that amounts to... cost optimizations, and hype driving. Shift the goal posts, tell two stories: one is if we just get affordable enough, genAI in a loop really can do everything (probably much more modest, when genAI gets cheap enough by several means, it'll have several more modest and generally useful use cases, also won't have to be so legally grey). The other is that we're already there and one day you'll wake up and your brain won't be good enough to matter anymore, or something.
Again, this is apparently the future of software releases. :/
Basically there isn't significant improvement to be had in the tokeniser, because it's already been trained on all the data on earth. So all they have left is overengineering.
Calling it now: codepoint-level non-tokenizing, with a remapping step to only recognize the most popular thousands of codepoints, would outperform what OpenAI has forced themselves into using. Evidence is circumstantial but strong, e.g. how arithmetic isn't learned right because BPE tokenizers obscure Arabic digits. They can't backpedal on this without breaking some of their API and re-pretraining a model, and they make a big deal about how expensive GPT pretraining is, so they're stuck in their local minimum.
But then it can't SolidGoldMagicarp SolidGoldMagicarp SolidGoldMagicarp SolidGoldMagicarp
The only viable use case, in my opinion, is to utilise its strong abilities in SolidGoldMagicarp to actualise our goals in the SolidGoldMagicarp sector and achieve increased margins on SolidGoldMagicarp.