They said (paraphrase) "we train the audio models on CC data because training on copyrighted data would be problematic." Thus, they imply that training on copyrighted images is also problematic — but they don't care because there's no strong lobby like RIAA there.
POLICY
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Audio Model Admissions and Copyright Law Discovery Issues
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Admitted it in interviews about the audio model. Many statements made are problematic if you look at them in the context of discovery. (About copyright law, yes. What about it?) https://
x.com/RedSagitter/st
atus/1614657872532766723
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Fair Use as Defense Against Copyright Infringement Claims
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They say "unauthorized copies" is that what you mean? If so, then it's an appropriate statement. Fair Use, which many in the community claim is at play here, is a defence you use to clear the liability of infringement — but the infringement is admitted.
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Smug Archive Cherry-Picks Technology Successes Ignoring Failures
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The Smug Archive
cherry-picks
ignores nukes & tech that has actually cause major harm (submachine guns, pesticides, etc)
ignores importance of regulation (seatbelts, airplane certification etc)
ignores tech that failed (full self-driving, Facebook M, dirigibles etc) https://
x.com/ylecun/status/
/ylecun/status/1614674331023413248
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Safeguards and Fair Compensation for AI-Generated Content
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Yes, I can understand that perspective. I think more safeguards and fair compensation need to be in place for that to work. e.g. adding a kNN search to all generated outputs to notify of infringement on training data, and dedicating 10% income to charities supporting artists.
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Three necessities to regulate evolving artificial intelligence
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Three necessities to regulate ever-evolving artificial intelligence – The Hill Read more here: https://
ift.tt/igVdAh9 #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Who Controls Generative AI Models: Power and Governance
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I predicted that 2023 would see a furore around training data. I think this may distract from even more important questions like: who controls the #generativeai models?
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OpenAI Research on Generative LM Disinformation Risks
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OpenAI publishes new work analyzing how generative LMs could potentially be misused for disinformation and how to mitigate these types of risks. 5 of 11
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Open Architecture vs Fair Data Compensation in AI
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Seems to me that there are two orthogonal issues:
– should your architecture be open? – where do you get your data from/are contributors justly compensated? Both are tricky. But virtue in one doesn’t logically entail virtue in the other. -
Superficial AI Progress Masks Deeper Problems and Misinformation Risks
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not in the areas that I have emphasized for over two decades. in my view we have tons of superficial progress, but little progress in the deeper problems that would get us to genuine and trustworthy intelligence. And are entering a mess of misinformation we are ill prepared for