Comment on Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away."
NaibofTabr@infosec.pub 14 hours agoEvery single generative tool is built on theft. No one has a training database that only contains code they were given legal permission to use for that purpose. Moreover, if these tools were trained on any GNU GPL code, then the tool and all of its output should also be GNU GPL:
if you distribute a derivative work or modification, you must provide the source code to those recipients under the same or equivalent license terms
en.wikipedia.org/wiki/GNU_General_Public_License
None of the companies developing these tools are obeying the terms of the licenses. The trained models are the product of theft.
You cannot be a moral person and approve of the use of these tools, they are diametrically opposed.
Hard disagree.
This is like saying anyone who has watched a Disney movie now owes Disney a check any time they illustrate anything, even entirely unrelated, because they’ve learned from their commercial products in the past. If they don’t pay Disney, then their creations are based on theft.
Digital reproduction is digital reproduction no matter how many extra steps are added to the reproduction process. It’s just an algorithm that sorts through a collection of stored data to find specific pieces of data which best fit the keywords supplied by the user, then regurgitates the results that are the best match based on correlation.
In spite of common meaning overlap and popular metaphors, the human brain is not a computer. Ask any neurologist.
Fundamentally that’s a purely ethical decision about whether a machine doing something should be treated with the same understanding the same as a human would. But we don’t consider remembering something with a neurochemical storage the samd as taking a picture of something even if they’re basically the same.
That’s because taking a picture is an idetic copy. Machine learning is NOT copying, it’s learning - hence the name.
This is a misunderstanding based on confusion between technical and colloquial terminology.
A machine learning model “learns” information in the same way that a curve fitting algorithm “learns” the shape of a data set.
This is not the same as the colloquial meaning of human learning. It is a mathematical process.
AwesomeLowlander@sh.itjust.works 13 hours ago
Given that you’ve presumably looked at open source code in the past, and got more proficient (however marginally) as a result, does all your future code now belong to the GPL?
NaibofTabr@infosec.pub 6 hours ago
This comparison is invalid. Training a neural network algorithm is not equivalent to human learning. We are talking about data stored in machine learning models owned and controlled by multi-billion dollar corporations.
It has already been demonstrated multiple times that original training data can be reproduced completely from models, so yes, they are data storage systems. When they reproduce code which they have previously stored, even only in part, that is a derivative work. Adding extra steps to the transcribing process doesn’t make it any less a copy of the original.
Epp@lemmus.org 4 hours ago
Only when the date in question is so oblique as to the original source being the only place in which the data exists, which is neither common, nor useful in practice.