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Comment by mobiuscog | Hacker News Reader

If it is not ruled fair use, or similar, all non-copyright countries are going to advance far faster. Whilst there are many ethical discussions to have, this will come down to the simple fact of there being people who will take the data anyway and thus have the advantage in datasets, assuming that matters.

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The US shot itself in the hand foot and ass by letting the wright brothers patent troll so hard that they couldn't even make their own planes during WW1, they were buying American designs built by France.

https://www.centennialofflight.net/essay/Aerospace/WWi/Aero5...

> The United States did not produce any aircraft of its own design for use at the front during World War I.

If it happens again for AI who knows what will happen.

You're making an assumption there, that "advance" is just one axis. There are many ways a society could "advance", many of which are wildly impeded by current AI technologies. I'm just not sold that it's a good technology to let run free without any regulation. (Heck, not many are.)

I think the ideal of more data == faster advancements may turn out to be a false equivalency. Similar to prior innovations, a healthy headcount, headstart and steady R&D funding will more likely make a difference.

Besides, rather than vacuuming up exisiting data, future resources might be better spent on creating bespoke datasets with user consent and content licensing baked in from the start.

> Besides, rather than vacuuming up exisiting data future resources might be better spent on creating bespoke datasets with user consent and content licensing baked in from the start.

Not mutually exclusive.

Probably not, but I think it is worthwhile to see if models can achieve sota with less, and if not, have individuals clearly onboard and informed of their data contributions.

We have conducted large statistical surveys in the past, so I see little reason why these and other established data collection practices could not be updated and utilised for refining contemporary models.

For DNA and genetics more data is better. Data and it's interpretation is the bottleneck for some subjects but not all. Getting more data from search engines about purchasing habits might not yield more/better results as MoE showed when 2-3 experts was better than 4-6.

At first, data is needed to overcome scarcity in domains where it has traditionally been difficult to obtain -- but I don't think it's quite the same as the 'data' being (colloquially) referred to here. We may want to discern between user generated content and genetic features that one has little influence in creating, among the many other data types and kinds.

It's probably a large reason why this space is so difficult to license/regulate: data to one may simply be 'noise' to another, or not even register as such. Definitions unfortunately, do not always map.

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