this post was submitted on 11 Jan 2024
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At a Senate hearing on AI’s impact on journalism, lawmakers backed media industry calls to make OpenAI and other tech companies pay to license news articles and other data used to train algorithms.

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[–] Grimy 55 points 1 year ago* (last edited 1 year ago) (15 children)

“What would that even look like?” asks Sarah Kreps, who directs the Tech Policy Institute at Cornell University. “Requiring licensing data will be impractical, favor the big firms like OpenAI and Microsoft that have the resources to pay for these licenses, and create enormous costs for startup AI firms that could diversify the marketplace and guard against hegemonic domination and potential antitrust behavior of the big firms.”

As our economy becomes more and more driven by AI, legislation like this will guarantee Microsoft and Google get to own it.

[–] Motavader 28 points 1 year ago* (last edited 1 year ago) (7 children)

Yes, and they'll use legislation to pull up the ladder behind them. It's a form of Regulatory Capture, and it will absolutely lock out small players.

But there are open source AI training datasets, but the question is whether LLMs can be trained as accurately with them.

[–] [email protected] 8 points 1 year ago (3 children)

Any foundation model is trained on a subset of common crawl.

All the data in there is, arguably, copyrighted by one individual or another. There is no equivalent open - or closed - source dataset to it.

Each single post, page, blog, site, has a copyright holder. In the last year big companies have started to change their TOS to make that they are able to use, relicense and generally sell your data hosted in their services as their own for the intent of AI training, so potentially some small parts of common crawl will be licensable in bulk - or directly obtained from the source.

This does still leave out the majority of the data directly or indirectly used today, even if you were willing to pay, because it is unfeasable to search and contract every single rights holder.

On the other side of it there have been work to use less but more heavily curated data, which could potentially generate good small, domain specific, models. But still they will not be like the ones we currently have, and the open source community will not be able to have access to the same amount and quality of data.

It's an interesting problem that I'm personally really interested to see where it leads.

[–] wikibot 3 points 1 year ago

Here's the summary for the wikipedia article you mentioned in your comment:

Common Crawl is a nonprofit 501(c)(3) organization that crawls the web and freely provides its archives and datasets to the public. Common Crawl's web archive consists of petabytes of data collected since 2008. It completes crawls generally every month.Common Crawl was founded by Gil Elbaz. Advisors to the non-profit include Peter Norvig and Joi Ito. The organization's crawlers respect nofollow and robots.txt policies. Open source code for processing Common Crawl's data set is publicly available. The Common Crawl dataset includes copyrighted work and is distributed from the US under fair use claims. Researchers in other countries have made use of techniques such as shuffling sentences or referencing the common crawl dataset to work around copyright law in other legal jurisdictions.As of March 2023, in the most recent version of the Common Crawl dataset, 46% of documents had English as their primary language (followed by German, Russian, Japanese, French, Spanish and Chinese, all below 6%).

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