Much as I dislike the theft of human labor that feeds many of the #generativeAI products we see today, I have to agree with @pluralistic that #copyright law is the wrong way to address the problem.

To frame the issue concretely: think of whom copyright law has benefited in the past, and then explain how it would benefit the individual creator when it is applied to #AI. (Hint: it won’t.)

Copyright law is already abused and extended to an absurd degree today. It already overreaches. It impoverishes society by putting up barriers to creation and allowing toll-collectors to exist between citizen artists and their audience.

*Labor* law is likely what we need to lean on. #unions and #guilds protect creators in a way that copyright cannot. Inequality and unequal bargaining power that lead to exploitation of artists and workers is what we need to address head-on.

Copyright will not save us.

“AI "art" and uncanniness”

https://pluralistic.net/2024/05/13/spooky-action-at-a-close-up/#invisible-hand

Here’s a clear example of how aggressive the image processing has become on newer iPhones. This is a comparison between the iPhone 15 Pro Max and the iPhone 11 Pro Max, taking photos of distant text at equal magnification. Note how the 15 Pro Max’s image pipeline has made up all the details.

EDIT: I’m going to drop mentions of “AI” and “hallucinating” here because I think it’s conjuring up the wrong mental models in readers’ heads. What’s likely happening is over-eager noise reduction and sharpening (which may or may not have pattern matching) creating details where none exist. Every phone does some amount of NR and sharpening, but later iPhones are super aggressive in this regard, so much so that the results often depart from what we accept as “reality”.

#apple #iphone #imageProcessing

Original video: https://www.facebook.com/watch?v=885196069752553

#AI #LLM is gunking up the web, especially for lesser-represented languages. Spammers are creating garbage English language content using LLMs, then translating it into *multiple languages* at the same time, using Machine Translation, presumably to generate clickbait ad revenue in several languages at once.

In English, such gunk accounts for some 9% of total sampled web content. But in languages with less representation on the Internet, the figures could be much higher. In Malay, it’s something like 26%, and in Swahili it’s nearly HALF of everything found on the web.

Paper [pdf]: “A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism”

https://arxiv.org/pdf/2401.05749.pdf

This is excellent reporting. Reuters somehow got their hands on seven years of internal #Tesla service records, as well as internal communications from service technicians and engineers.

What they found is pretty shocking to me. Repeated catastrophic failure of suspension parts. Power steering suddenly disabling itself. Evidence of denying warranty coverage. Failures that forced a recall in China that continued to be shipped in the US.

Pretty damning stuff.

#cars

“Tesla blamed drivers for failures of parts it long knew were defective”

https://www.reuters.com/investigates/special-report/tesla-musk-steering-suspension/