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bingbingbing777 | 1 year ago

Why are you so frustrated that a company decided to not completely release something they have built internally?

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yterdy|1 year ago

Because, half a century ago, it would have been built by a government research agency or a designated monopoly that was obliged to share it with the public, instead of the quasi-monopoly - that can keep secret whatever it needs to wreck your sh*t - like today.

We know a better way to do this ("this" being "the development of foundational technology for the next century of human civilization"), so of course it's frustrating to see the way it's actually being done.

392|1 year ago

What's the better way?

GaggiX|1 year ago

Because it's presented as research, but the results are not reproducible without at least information about the dataset.

fngjdflmdflg|1 year ago

It is reproducible with the dataset though. (Or more accurately may be reproducible). It is important to distinguish between "reproducibility" meaning "the extent to which consistent results are obtained when an experiment is repeated" and "the ability to be reproduced or copied." Only the former is necessary for an experiment to be considered reproducible. It's just that it may be difficult to actually run the experiment although certainly not impossible, at least if we consider using a similar alternative dataset as its really the coed being tested here. But in any event I think it qualifies as publishing research all the same. Also note that research is still research even if it not published.

nolok|1 year ago

Well Google did that for years and where did that get them? To companies using their research to build something but not share to the same extent their research so they could keep a leg up.

So yeah, they learned their lesson. You want to complain, complain to those who did not play the game fair and square.

vessenes|1 year ago

GaggiX has it mostly right below. But, I'm frustrated because I'd like to try this out. And, by try it out, any of these would be fine:

1. Download the datasets and train a small version to get a feel for it.

2. Download the models and deploy them to use it and get a feel for it.

3. Talk to it via a paid API

Why do I want to do that? I'd like to know how capable this architecture is, and get a feel for how capable it could be with different data / scale up / fine tuning, etc.