Maybe the ice cream was just that good, and GAP was lucky to be able to sell their polo shirts to ice cream enthusiasts who'd otherwise have bought them at Old Navy.
> Wrong answer. The ice cream and chocolate store was in competition with every other store in the mall. Time or money spent at the GAP can't be time or money spent here.
Was the interviewer a macroeconomics grad student working his way through school at the ice cream shop? Because I can't imagine anyone but a macroeconomics student aggregating all demand into a generic concept of "time and money" without regard for qualitative distinctions between entirely different product categories.
Did he also think the shop was in competition with United Airlines or the local dentist's office, because time and money spent on a trans-Atlantic flight or getting a root canal was time and money that couldn't be spent at the ice cream shop?
> Whether or not people are using LLMs for news specifically, any new, large eater of eyeball-time is going to hurt the business landscape for all other eyeball harvesters.
Which demonstrates that the model of treating the content users are looking for as bait so you can sell their attention to someone else was always an adversarial one in the first place.
Users themselves were never looking for time sinks, they were looking for specific information or experiences that they've had to increasingly endure time sinks to get to due to the perverse incentives in the social media landscape.
AI destroying the viability of "eyeball harvesters" as a business model is an opportunity for people actually creating interesting content, not engagement-maximizing filler, to pivot back to pitching quality directly to their users. That's exactly the point that Tim Ferriss was making in the article: he points out that he already prefers to sell his books to a niche audience of 10,000 readers who actually find value in them than try to engage with 10 million passers-by on social media.
AUR isn't a package repo. It's a collection of user-contributed PKGBUILD scripts, to make building packages from upstream source distributions more convenient. It's not meant to be treated like an official repo of binary packages.
It's quite interesting, and describes how the developer used COBOL to implement a raycasting algorithm and generate a stream of PPM images to to pipe into FFplay. There's zero evidence of this being written in Claude; there are multiple clips of the developer working in VSCode, where the Claude plugin doesn't even appear to be installed.
> It wasn’t that long ago that American racists debated whether Italians and even Irish were truly “white.” The definition of white had expanded considerably over the years.
Eastern Europeans, Jews (of course), and Russians were also at times not “white.”
This idea is mostly a modern fabrication. Various more granular ethnic biases were of course present throughout American history, but those were never conflated with racial categories: in times and places where the white vs. black racial division was relevant, the ethnic groups you're referencing were always considered "white".
And the types of discrimination that people in white ethnic groups sometimes experienced was of of a type and of a degree vastly different from that experienced by black people. They're really two very distinct phenomena, and weren't evenly distributed throughout the US -- black people in the South had the legacy of slavery, Jim Crow segregation, and other horrifying things to deal with, whereas white immigrant communities in the Northeast or Midwest never experienced anything remotely similar.
> The camera analogy is a good one but I have never had a camera that had every great picture somebody else had taken, plus every work of art, baked into it.
I've never had an LLM that had any of that baked into it either. LLMs just have token correlations trained on those works. Trying to get an LLM to output the data it was trained on verbatim is something I'd expect to be heading into monkeys-on-typewriters territory. "Write something in the style of Shakespeare" and "give me the original text of Hamlet" are two very different things.
> I agree with the framing of the AI as a tool not an autonomous entity. The thing is, to me, it is exactly that framing that makes it so the use of that tool means "copying" more than it means "learning and taking inspiration and creating new art", because who is doing the learning and being inspired?
It's not learning or taking inspiration, though. It's just making statistical inferences based on token correlations. Whether or not that's analogous to how humans learn is something I think is a metaphysical question that is of little practical relevance. The fact remains that LLMs are not human, have no intentions of their own, do not exercise any kind of agency despite how often people employing the misnomer "agentic", and are ultimately glorified statistical models.
The LLM is a tool that extends human capacities in the same way as any other mathematical framework or technological device.
> I think of a trained AI like a lossy, highly compressed copy of its training data set.
I've seen a few people in this thread make that argument, but I just can't agree with it. It's not compression, lossy or lossless, which aims to deterministically encode a representation of the specific input data. The training data is analogous to the sample set used in a regression analysis to generate a polynomial function -- it's not valid to treat the output from any application of that polynomial as a copy of the original sample data.
> It was the first time I can say that installing a linux OS was easier and friendlier than Windows.
I'd say that from work experience managing an IT department that maintains and deploys both Windows and Linux machines, the administrative overhead involved in working with Windows first exceeded that of Linux at some point in the Windows 10 life cycle -- at least five years ago. Since then, Windows has been getting worse and worse, and Linux has been getting better and better.
With most corporate software being accessible via the web and/or being cross-platform these days, we're seriously debating moving the standard corporate workstation configuration to Linux.
> But try to write your own story of a lion cub chased away by his uncle and living in a jungle until his childhood friend finds him and convinces him to reclaim his kingdom, and you'll quickly hear from Disney's lawyers how non-derivative it really is.
I'd expect them to say "we don't like this, but since it's not actually a derivative work, we can't do anything about it". As long as you're not directly copying things like characters, dialogue, etc., it's not a derivative work.
That's why Armageddon is not a derivative work of Deep Impact, the Shark Attack series is not a derivative work of Jaws, the more famous Titanic is not a derivative work of 1979's S.O.S. Titanic, and the Harry Potter series is not a derivative work of Teen Witch.
Using the same story themes, plot points, and setting as another work does not implicate that other work's copyright. Only substantial copying of specifics does.
> under the condition that if you use it for anything, I get credited; else, you get nothing.
But this has never been a condition in the FOSS world, as far as I'm aware. I've only ever seen attribution requirements attach to redistribution of source, not usage of the software.
I understand that the crux of the debate here is whether training an LLM is redistribution of the underlying code, but to me, it seems to be fairly clear that it is not.
> Luckily, FOSS is specific published works, and unless LLMs actually reasonably-provably do such decomposing into ideas/facts (good luck reasoning about that), that part is also irrelevant.
That's literally all LLMs do. That's what tokenization is. And it's trivially provable, since if you compare LLM models with the copyrighted works you're claiming they replicate, all you'll see on the LLM side is probability matrices representing correlations between decomposed units of knowledge aggregated across the entire dataset as an integrated whole.
> Depending on intent, that very much can happen, it's called plagiarism. Good luck proving an LLMs intent.
The only intent ever in play is that of the user. LLMs are just software.
> But it does exist, and within this framework, the creator gets to say how you may redistribute their IP,
Right. And the way the creator gets to exercise that say is by releasing their work under a license. If you release your work under a FOSS license, you're saying "you are free to copy this work and use it for your own purposes".
Complaining that people are using it for purposes you don't like after you've already given permission to them to use it for whatever purposes they please seems a bit disingenuous.
> and "We compressed it very much" isn't an out.
It's not, but I don't think we're discussing that. We're talking about LLMs, not people redistributing zip files containing someone else's work. If you're trying to imply that LLMs are merely a form of compression, that's a position you've got to argue for, because I'm definitely not seeing any similarity between the two.
> If you put a GPL C program through Emscripten to run in a browser the output doesn't include the original C code but it's surely a derivative work.
Because it does include content from the original work -- this is just a translation, and isn't comparable to how LLMs work.
> To me the answer is simply that humans are special.
I don't disagree, but I also view LLMs as tools that extend human capacities and not autonomous entities unto themselves. LLMs are still just software, and can't really be regarded as anything other than instruments that humans use to broaden their capacity to see, appreciate, understand, and draw on that experience in what they create.
> That may seem remarkably unfair to the machines, or like a cop-out.
No, it's unfair to the humans. The machines are just tools that they use. The "double standard" is really a set of inconsistent standards applied to the same underlying moral agents.
> After all, if you want to treat a machine exactly like a human who learns from prior art to create new art, then the ownership of the new art would also belong to the machine. Not to the person who prompts it.
No, it always belongs to the person who prompts it. The machine is not a conscious entity, bears no intentions, and has no capacity to act on its own initiative. The machine is always just a tool that extends human capacity, as all machines always have.
For a good comparison here, we've never not credited a photographer as the author of a photograph. But the photographer is in a sense merely prompting the camera by framing the shot, selecting the exposure, adjusting the lighting, etc. -- the hard work in actually creating the photograph is being done by the camera itself, with the photographer playing no role in directly constructing the final image, and with the many of the qualities of the final image being determined by pre-existing features of the camera's functional design and components that the photographer also played no role in defining, apart from choosing which camera to use.
LLMs are like cameras in this way. And the fact that they rely on external data for model training no more disclaims the user as the author of the resulting work than looking things up in a dictionary or encyclopedia does the same for the author of an essay.
I mean, the most restrictive license, the GPL, was conceived specifically to protect the "four freedoms" and prevent subsequent modifications from violating them. The "copyleft" concept was specifically designed to create an ecosystem that behaved as if copyright didn't apply in the first place.
I don't know how you can imply with a straight face that it did anything else.
I don't know how you can possibly argue that non-redistributive usage of software could ever violate the GPL -- and the other common FOSS licenses don't even have the copyleft provision, and literally are saying "do whatever you want, but I'm not responsible".
No, it isn't. A derivative work isn't something based on extracting underlying ideas or patterns from another work, it's something that includes copyrighted portions of the other work.
An annotated edition of Hamlet is a derivative work. A Cliff's Notes summary of Hamlet is a derivative work.
Strange Brew and The Lion King are not derivative works of Hamlet simply because they include literary themes and plot points that originated in Hamlet. A list of word counts of popular works of literature that includes an entry for Hamlet is also not a derivative work. The Markov chain described above is not a derivative work.
> The obvious follow up here is whether an LLM is creating transformative derivations or not. A lot of folks argue that yes, an LLM spitting out statistically sampled code that matches existing code is not transformative and is (or might be) infringing the terms of the license it was released under.
And I would agree with them. An LLM that actually is outputting non-trivial code that matches a public project's code verbatim is engaging in copying, and not stochastic inference.
> I think it's a pretty obvious "somewhere in the middle" that is gonna make a bunch of lawyers a whole lot of money.
It's a shame that the same fundamental questions have to be relitigated over and over again just because the contextual formalities and modes of expression have changed. I wonder how many of the legal cases are going to be copies or derivative works of previous ones.
> That's wrong. What on earth gave you that impression when the licenses specifically set constraints on what downstream can do (from "release derivatives as open" to "put me in the credits").
These are restrictions on redistribution, not use. And they're there to make sure that derivative works can't themselves impose restrictions on use.