341–350 of 408 posts
If you have a company that depends on software, the rest of the business (service, reliability, etc) better be rock solid because you can be guaranteed someone will do a rewrite of your stack.
I like the idea of AI-generated ~code~ anything being public domain. Public data in, public domain out.
Lawyer here. Its not. This article is highly confused. The case was about whether an AI could be considered an author for copyright purposes. Mainly as a way of arguing for robot rights, not copyright. The person listed the AI as the sole author: On the application, Dr. Thaler listed the Creativity Machine as the work’s sole author and himself as just the work’s owner. This is not the first time someone tried to say…
Did you reply to the wrong comment? I was just saying I like the idea of AI-generated anything being public domain, not that it currently is/isn't.
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SCOTUS hasn't ruled on any AI copyright cases yet. But they've said in Feist v Rural (1991) that copyright requires a minimum creative spark. The US Copyright Office maintains that human authorship is required for copyright, and the 9th Circuit in 2019 explicitly agreed with the law that a non-human animal cannot hold any copyright. Functionally speaking, AI is viewed as any machine tool. Using, say, Photoshop to dra…
The lack thereof (of human use). Prompts are not copyrightable thus the output also - not. Besides retelling a story is fair use, right? Otherwise we should ban all generative AI and prepare for Dune/Foundation future. But we not there, and we perhaps never going to be. So the LLM training first needs to be settled, then we talk whether retelling a whole software package infringes anyone's right. And even if it does,…
Actually, most of the time, it is not.
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Yes, this is the reason I've completely stopped releasing any open-source projects. I'm discovering that newer models are somewhat capable of reverse-engineering even compiled WebAssembly, etc. too, so I can feel a sort of "dark forest theory" taking hold. Why publish anything - open or closed - to be ripped off at negligible marginal cost?
It’s a real problem. I threw it at an old MUD game just to see how hard it is [0] then used differential testing and LLMs to rewrite it [1]. Just seems to be time and money. [0] https://reorchestrate.com/posts/your-binary-is-no-longer-saf... [1] https://reorchestrate.com/posts/your-binary-is-no-longer-saf...
Did you find it worked reasonably well on any portion of the codebase you could throw at it? For example, if I recall correctly, all of MajorMUD's data file interactions used the embedded Btrieve library which was popular at the time. For that type of specialized low-level library, I'm curious how much effort it would take to get readable code.
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“Changing the equation” by boldly breaking the law.
> “Changing the equation” by boldly breaking the law. Is it? I think the law is truly undeveloped when it comes to language models and their output. As a purely human example, suppose I once long ago read through the source code of GCC. Does this mean that every compiler I write henceforth must be GPL-licensed, even if the code looks nothing like GCC code? There's obviously some sliding scale. If I happen to commit l…
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This reminds me of a full rewrite. When a developer reimplements a complete new version of code from scratch, with an understanding only, a new implementation generally should be an improvement on any source code not equal. In today’s world, letting LLMs replicate anything will generate average code as “good” and generally create equivalent or more bloat anyways unless well managed.
The world is chock-full of rewrites that came out disastrously worse than the thing they intended to replace. One of Spolsky's most-quoted articles of all time was about this. https://www.joelonsoftware.com/2000/04/06/things-you-should-... > They did it by making the single worst strategic mistake that any software company can make: They decided to rewrite the code from scratch.
Finding a middle ground of building a roadmap to refactoring your way forward is often much better.
Appreciate the Joel link, nice to see that kind of stuff again.
With that being said if it's the same small team that built the first version, there can be a calculated risk to driving a refactor towards a rewrite with the right conditions. I says this because I have been able to do it in this conditions a few times, it still remains very risky. If it's a new or different team later on trying to rewrite, all bets are off anyways.
We have to remember 70% of software projects fail at the best of times, independent of rewrites.
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Turns out there’s no need to speculate. Someone pointed out on GH [0] that the AI was literally prompted to copy the existing code: > *Context:* The registry maps every supported encoding to its metadata. Era assignments MUST match chardet 6.0.0's `chardet/metadata/charsets.py` at https://raw.githubusercontent.com/chardet/chardet/f0676c0d6a... > Fetch that file and use it as the authoritative reference for which enco…
That's data, not code.
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Turns out there’s no need to speculate. Someone pointed out on GH [0] that the AI was literally prompted to copy the existing code: > *Context:* The registry maps every supported encoding to its metadata. Era assignments MUST match chardet 6.0.0's `chardet/metadata/charsets.py` at https://raw.githubusercontent.com/chardet/chardet/f0676c0d6a... > Fetch that file and use it as the authoritative reference for which enco…
That's data, not code.
The maintainer's response: https://github.com/chardet/chardet/issues/327#issuecomment-4... The second part here is problematic, but fascinating: "I then started in an empty repository with no access to the old source tree, and explicitly instructed Claude not to base anything on LGPL/GPL-licensed code." Problem - Claude almost certainly was trained on the LGPL/GPL original code. It knows that is how to solve the prob…
You've likely paid attention to the litigation here. Regardless of what remains to be litigated, the training in and of itself has already been deemed fair use (and transformative) by Alsup. Further, you know that ideas are not protected by copyright. The code comparison in this demonstrates a relatively strong case that the expression of the idea is significantly different from that of the original code. If it were…
Can I use one AI agent to write detailed tests based on disassembled Windows, and another to write code that passes those same function-level tests? If so, I'm about to relicense Windows 11 - eat my shorts, ReactOS!
The maintainer's response: https://github.com/chardet/chardet/issues/327#issuecomment-4... The second part here is problematic, but fascinating: "I then started in an empty repository with no access to the old source tree, and explicitly instructed Claude not to base anything on LGPL/GPL-licensed code." Problem - Claude almost certainly was trained on the LGPL/GPL original code. It knows that is how to solve the prob…
There was a paper that proposed a content based hashing mask for traning The idea is you have some window size, maybe 32 tokens. Hash it into a seed for a pseudo random number generator. Generate random numbers in the range 0..1 for each token in the window. Compare this number against a threshold. Don't count the loss for any tokens with a rng value higher than the threshold. It learns well enough because you get th…
I think it's more subtle than that. IIUC the tokens were all present for the purpose of computing the output and the score is based on the output. It's only the weight update where some of the tokens get ignored. So the learning is lossy but the inference driving the learning is not.
Rather than a book that's missing words it's more like a person with a minor learning disability that prevents him from recalling anything perfectly.
However it occurs to me that data augmentation could easily break the scheme if care isn't taken.