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That's great news, but one would think that since they're behind Stable Diffusion, that they'd use the insights behind it and scale data even more than that to

That's great news, but one would think that since they're behind Stable Diffusion, that they'd use the insights behind it and scale data even more than that to result in better quality at a smaller scale model that can run on most people's machines. Like... try 10 trillion or 100 trillion tokens (although that may be absurd, I never did the calculation), and a long context on a 7B parameter model then see if that gets you better results than a 30 or 65B parameter on 1.5 trillion tokens. A lot of these open source projects just seem to be trying to follow and (poorly) reproduce OpenAI's breakthroughs instead of trying to surpass them.

dragonwriter 4y ago
> Like... try 10 trillion or 100 trillion tokens (although that may be absurd, I never did the calculation) But where’s the corpus supposed ro come from?
GaggiX 4y ago
>try 10 trillion or 100 trillion tokens Computation is not free and data is not infinite.
- youssefabdelm 4y ago
  You could've said the same to OpenAI when they were scaling GPT from 1 billion to 175 billion parameters. We're all grateful they didn't follow that line of thought. But Stability does have access to a pretty big cluster, so it's not paying cloud compute (I assume), so cost will be less, and data of course is not infinite...never stated that. But considering 3.7 million videos are uploaded to youtube everyday, 2 million scientific articles published every year, yada yada...that argument falls apart. At the very least implement spiral development... 1 trillion... 3 trillion... (oh it seems to be getting WAY better! There seems to be a STEP CHANGE!)... 5 trillion... (holy shit this really works, lets keep going)
  - dragonwriter 4y ago
    The training corpus is the problem. An extra trillion tokens is (ballpark) an extra million KJV bibles worth of text formatted for ingestion. And you probably picked all of the low hanging fruit in terms of quality prior vetting and being in a standard format for ingestion in your first trillion tokens of training data.
  - taneq 4y ago
    There’s a difference between telling someone they’re wasting their time with their current project, and asking them why they didn’t spend 6x - 60x as much budget on an already expensive project.
    - youssefabdelm 4y ago
      They're loaded, and we know scaling works, they'd massively benefit... both in marketing and profit. Although it is open source to be fair.
Taek 4y ago
Nobody knows where to find 10 trillion tokens of good data. Publicly available / data without a license seems to cap at around 1.5 trillion tokens total. The internet isn't as big as you thought! (Or at least, all the good stuff is behind a walled garden, which I think we did know)

dragonwriter 4y ago

> Like... try 10 trillion or 100 trillion tokens (although that may be absurd, I never did the calculation) But where’s the corpus supposed ro come from?

GaggiX 4y ago

>try 10 trillion or 100 trillion tokens Computation is not free and data is not infinite.

youssefabdelm 4y ago
You could've said the same to OpenAI when they were scaling GPT from 1 billion to 175 billion parameters. We're all grateful they didn't follow that line of thought. But Stability does have access to a pretty big cluster, so it's not paying cloud compute (I assume), so cost will be less, and data of course is not infinite...never stated that. But considering 3.7 million videos are uploaded to youtube everyday, 2 million scientific articles published every year, yada yada...that argument falls apart. At the very least implement spiral development... 1 trillion... 3 trillion... (oh it seems to be getting WAY better! There seems to be a STEP CHANGE!)... 5 trillion... (holy shit this really works, lets keep going)
- dragonwriter 4y ago
  The training corpus is the problem. An extra trillion tokens is (ballpark) an extra million KJV bibles worth of text formatted for ingestion. And you probably picked all of the low hanging fruit in terms of quality prior vetting and being in a standard format for ingestion in your first trillion tokens of training data.
- taneq 4y ago
  There’s a difference between telling someone they’re wasting their time with their current project, and asking them why they didn’t spend 6x - 60x as much budget on an already expensive project.
  - youssefabdelm 4y ago
    They're loaded, and we know scaling works, they'd massively benefit... both in marketing and profit. Although it is open source to be fair.

Taek 4y ago

Nobody knows where to find 10 trillion tokens of good data. Publicly available / data without a license seems to cap at around 1.5 trillion tokens total. The internet isn't as big as you thought! (Or at least, all the good stuff is behind a walled garden, which I think we did know)