Battleagainstentropy
Battleagainstentropy t1_j96iltm wrote
Reply to comment by TransitoryPhilosophy in [D] Lack of influence in modern AI by I_like_sources
Yes this reads like an undergrad or someone entirely outside the field who thinks that no one has thought of these concepts before. They are trying a little Cunningham’s Law by stating that nothing is being done in these areas and hoping that someone provides the correct information rather than simply ask the question of what is being done to address these issues.
Battleagainstentropy t1_is0vlku wrote
Reply to comment by likeamanyfacedgod in [D] Career advice: Can one make a career in building machine learning models and then selling the IP for them? by likeamanyfacedgod
Most companies for whom this would be valuable have professional teams that would be working on this problem. What is your advantage over them building it internally? Do you have access to some resource like data that the industry doesn’t? This kind of thing exists for sure, but it’s typically started by people who are in the industry already, understand from the inside what the weaknesses and blind spots are of existing state of the art, then go off on their own to address them.
Battleagainstentropy t1_j9lpzkd wrote
Reply to [R] Provable Copyright Protection for Generative Models by vyasnikhil96
This is really interesting work. I wonder how meaningful these metrics can be made. For example, if I write a book about Harry Potter, the expert mug maker, then your metric is x. If I write about Barry Blotter, the boy wizard at Smogwarts, then your metric is y. IANAL but I think that the value needed to prove derivative work is a question of fact that would be up to a jury to decide, so being able to explain such a metric to laypeople could make this work. It’s somewhat similar to the way that DNA testing required a certain amount of education for juries (one in a million match and all that)