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Cake day: June 12th, 2023

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  • I’m using the radar network for dispatch and priority for tie breaking/to make sure the resources are distributed evenly.

    All my loading stations are simply called “Cargo Pickup” and all of my cargo trains go to any of them with an opening. Once there, the station reports on the red wire the ID of the train in the channel corresponding to the item being loaded (unless another train is already being reported by another station with the same items).

    On the demand side, stations look for the ID on the item they need. They copy the ID into the green network on the channel corresponding to their station name. In the simple case, a station serving copper ore to copper smelters copies the train ID from copper on the red network to copper on the green network. But stations can also request multiple ingredients in which case they have some other symbol in their name besides copper ore. (Of course, here too the copying only happens if no other station is requesting a train on that same channel).

    Back on the supply side, the station looks through all the IDs on the green network and sends the ones that match the waiting train to the train. The train uses the symbols to activate an interrupt to go to the corresponding station to deliver the goods.

    I just set this up today. I haven’t perfected it yet. One minor hiccup is handling the fact that you have no way to atomically access a channel. So two stations could request on the same channel at the same time, corrupting the ID. But that only happens if the stations are activated to make a demand on the exact same tick. It’s not so much that it’s a constant problem, it just bothers me that it could be.












  • When you use (read, view, listen to…) copyrighted material you’re subject to the licensing rules, no matter if it’s free (as in beer) or not.

    You’ve got that backwards. Copyright protects the owner’s right to distribution. Reading, viewing, listening to a work is never copyright infringement. Which is to say that making it publicly available is the owner exercising their rights.

    This means that quoting more than what’s considered fair use is a violation of the license, for instance. In practice a human would not be able to quote exactly a 1000 words document just on the first read but “AI” can, thus infringing one of the licensing clauses.

    Only on very specific circumstances, with some particular coaxing, can you get an AI to do this with certain works that are widely quoted throughout its training data. There may be some very small scale copyright violations that occur here but it’s largely a technical hurdle that will be overcome before long (i.e. wholesale regurgitation isn’t an actual goal of AI technology).

    Some licensing on copyrighted material is also explicitly forbidding to use the full content by automated systems (once they were web crawlers for search engines)

    Again, copyright doesn’t govern how you’re allowed to view a work. robots.txt is not a legally enforceable license. At best, the website owner may be able to restrict access via computer access abuse laws, but not copyright. And it would be completely irrelevant to the question of whether or not AI can train on non-internet data sets like books, movies, etc.




  • a much stronger one would be to simply note all of the works with a Creative Commons “No Derivatives” license in the training data, since it is hard to argue that the model checkpoint isn’t derived from the training data.

    Not really. First of all, creative commons strictly loosens the copyright restrictions on a work. The strongest license is actually no explicit license i.e. “All Rights Reserved.” No derivatives is already included under full, default, copyright.

    Second, derivative has a pretty strict legal definition. It’s not enough to say that the derived work was created using a protected work, or even that the derived work couldn’t exist without the protected work. Some examples: create a word cloud of your favorite book, analyze the tone of news article to help you trade stocks, produce an image containing the most prominent color in every frame of a movie, or create a search index of the words found on all websites on the internet. All of that is absolutely allowed under even the strictest of copyright protections.

    Statistical analysis of copyrighted materials, as in training AI, easily clears that same bar.