238 karma · joined April 14, 2020
I also believe that this statement is weird. I have a very shallow knowledge of ML, but I can imagine that in a convolutional neural network a training sample interacts with lots of parameters. This 'one training sample <-> one parameter' correspondence seems wrong to me.
The tradeoffs depend on the complexity of the Prolog code and your needs for performance and features: pure LP, Prolog (search+unification+cut), garbage collection, dynamic database updates, constraint domains, etc. The Ciao Prolog engine is around 300-400KB. Adding a few libraries, compiler, etc. it goes to 2MB. Naive Prolog systems can be one order of magnitude smaller at the cost of sacrificing ISO compatibility, performance, etc. Note that "performance" can be very misleading. Some Prolog programs may run particularly fast in some Prolog system and very badly in others.
(Congrats to Alyssa and everyone making this possible!)
This is a fallacy.
Why is recognizing someone else's work so much pain?
The whole point is that copilot forgets who wrote the code and who is the author of the whole idea (unfortunately few programmers write it but sometimes it is there is you are patient enough to read documentation). Thus a copilot's user cannot know who deserves the credit.
This whole discussion is like if you train an AI to pick apples from a supermarket and leave them on the street waiting for someone else to take them home, and pretending that nobody is stealing anything.
Would this kind of copying be fine in software and not in other scientific papers or other industrial processes? Would it be fine if I train copilot on a patent database and start creating new patents (at a rate in which is would be unpractical to determine that it is regurgitating prior art)?
What is the copyright of code written with copilot? Copilot learns the code and forgets authors.
Would you agree if I take your open source project, learn piece by piece, rewrite it from scratch and put my name on it without a single word about your work?
I do not care if it breaks code to bits and recomposes them again regurgitated by <YOUR-LATEST-AI-TECHNIQUE-HERE> in a way that is untraceable: it would not work without learning from our open source code. Code produced by this method should be automatically licensed under the most restrictive license of its input used for learning.
[1] Collage (/kəˈlɑːʒ/, from the French: coller, "to glue" or "to stick together";[1]) is a technique of art creation, primarily used in the visual arts, but in music too, by which art results from an assemblage of different forms, thus creating a new whole.
In the same way that some kids are good at sports, drawing, music, foreign languages, or playing videogames, some of them are very good managing abstractions. Those would be very happy learning calculus or other advanced mathematics, just for fun!