4 ms·
Claiming to care deeply about IP theft in the more nebulous case of model training datasets then dismissing the extremely concrete case of outright theft seems
by some_random 1y ago
Claiming to care deeply about IP theft in the more nebulous case of model training datasets then dismissing the extremely concrete case of outright theft seems pretty indefensible to me.
- perching_aix 1y agoPar for the course for emotional thinking, I'm not even surprised anymore.
- Arainach 1y agoEveryone has a finite amount of empathy, and I'm not going to waste any of mine on IP thieves complaining that someone stole their stolen IP from them.
- mensetmanusman 1y agoIt’s theft in the way taking a picture of nature that you had nothing to do with is theft.
- Arainach 1y agoThis line of argument was worn out and tired when 14 year olds on Napster were parroting it in 1999.
- some_random 1y agoI'm not asking you to cry or even stifle a laugh, the only think I'm criticizing is an uneven application of claimed values. Edit: Or an argument as to why this IP theft is fine while that used in training isn't. I'm sure some of that training data was CC-SA licensed for instance ;)
- pton_xd 1y ago> dismissing the extremely concrete case of outright theft seems pretty indefensible to me. Outright theft is a meaningless term here. The new rules are different. The AI space is built on "traditionally" bad faith actions. Misappropriation of IP by using pirated content and ignoring source code licenses. Borderline malicious website scraping. Recitation of data without attribution. Copying model code / artifacts / weights is just the next most convenient course of action. And really, who cares? The ethical operating standards of the industry have been established.