Yes, if Epic sold an Epic computer which had > 50% marketshare and and you could only purchase products from their store.
The only other category you can really compare this to is game consoles, but the hardware is sold at a much smaller margin and they still (for now) support physical media.
They do. Where did you get this? All the providers have clauses like this:
"4.1. Generally. Customer and Customer’s End Users may provide Input and receive Output. As between Customer and OpenAI, to the extent permitted by applicable law, Customer: (a) retains all ownership rights in Input; and (b) owns all Output. OpenAI hereby assigns to Customer all OpenAI’s right, title, and interest, if any, in and to Output."
The outputs of AI are most likely in the public domain. As automated process output are public domain, and the companies claim fair use when scraping, making the input unencumbered, too.
It wouldn't be OpenAI holding copyright - it would be no one holding copyright.
That would be considered a derivative work of the C code, therefore copyright protected, I believe.
Can you replay all of your prompts exactly the way you wrote them and get the same behaviour out of the LLM generated code? In that case, the situation might be similar. If you're prodding an LLM to give you a variety of resu
But significantly editing LLM generated code _should_ make it your copyright again, I believe. Hard to say when this hasn't really been tested in the courts yet, to my knowledge.
The most interesting question, to me, is who cares? If we reach a point where highly valuable software is largely vibe coded, what do I get out of a lack of copyright protection? I could likely write down the behaviour of the system and generate a fairly similar one. And how would I even be able to tell, without insider knowledge, what percentage of a code base is generated?
There are some interesting abuses of copyright law that would become more vulnerable. I was once involved in a case where the court decided that hiding a website's "disable your ad blocker or leave" popup was actually a case of "circumventing effective copyright protection". In this day and age, they might have had to produce proof that it was, indeed, copyright protected.
"Can you replay all of your prompts exactly the way you wrote them and get the same behaviour out of the LLM generated code? In that case, the situation might be similar. If that's not the case, probably not." Yes and no. It's possible in theory, but in practice it requires control over the seed, which you typically don't have in the AI coding tools. At least if you're using local models, you can control the seed and have it be deterministic.
That said, you don't necessarily always have 100% deterministic build when compiling code either.
That would be interesting. I don't believe getting 100% the same bytes every time a derivative work is created in the same way is legally relevant. Take filters applied to copyright protected photos - might not be the exact same bytes every time you run it, but it looks the same, it's clearly a derivative work.
So in my understanding (not as a lawyer, but someone who's had to deal with legal issues around software a lot), if you _save_ all the inputs that will lead to the LLM creating pretty much the same system with the same behaviour, you could probably argue that it's a derivative work of your input (which is creative work done by a human), and therefore copyright protected.
If you don't keep your input, it's harder to argue because you can't prove your authorship.
It probably comes down to the details. Is your prompt "make me some kind of blog", that's probably too trivial and unspecific to benefit from copyright protection. If you specify requirements to the degree where they resemble code in natural language (minus boilerplate), different story, I think.
(I meant to include more concrete logic in my post above, but it appears I'm not too good with the edit function, I garbled it :P)
Copyright'd in, copyright out. Your compiled code is subject to your copyright.
You need "significant" changes to PD to make it yours again. Because LLMs are predicated on massive public data use, they require the output to PD. Otherwise you'd be violating the copyright of the learning data - hundreds of thousands of individuals.
No, and your comment is ridiculously bad faith. Courts ruled that outputs of LLMs are not copyrightable. They did not rule that outputs of compilers are not copyrightable.
I think that lawsuit was BS because it went on the assumption that the LLM was acting 100% autonomously with zero human input, which is not how the vast majority of them work. Same for compilers... a human has to give it instructions on what to generate, and I think that should be considered a derivative work that is copyrightable.
I would say all art is derivative, basically a sum of our influences, whether human or machine. And it's complicated, but derivative works can be copyrighted, at least in part, without inherently violating any laws related to the original work, depending on how much has changed/how obvious it is, and depending on each individual judge's subjective opinion.
The sensible options were that either LLM outputs are derivative of all their training data, or they're new works produced by the machine, which is not a human, and therefore not copyrightable.
Courts have decided they're new works which are not copyrightable.
There is overall no health benefit since the hypoxic phase is quite long and creates stress during a time when the body is supposed to rest and recover. And that compounds with the underlying issue, usually mouth breathing, bad pillow, bad sleeping position, or a combination of these.
Mouth breathing is not a cause of sleep apnea, but it can be a consequence. Bad pillows and bad sleeping positions aren't causes of sleep apnea either, but some people do have "positional sleep apnea" where the apnea is (usually) much worse on the back and much better on the side.
One can also have sleep apnea without ever experiencing hypoxia. Drops in oxygen saturation during hypopneas are very minimal, and pretty much nonexistent with respiratory effort related arousals (RERAs). Not breathing is bad, but for many people with sleep apnea, the problem is the constant arousals and the lack of decent sleep, not a lack of oxygen.
IaaC code is one of those use cases just throwing LLM is painful for a refactor.
In my experience claude/codex to wrangle CDK constructs be complicated, it frequently hallucinates constructs that simply do not exist, options that are not supported etc.
While they can generate IaaC component mostly okay and these problems can be managed, Iterations can take a lot of time, each checkpoint, goes the deploy/ rollback cycles in CF. CloudFormation is also not particularly fast, other IaaC frameworks are not that different.
Running an agent to iterate until it gets it right is just more difficult with IaaC refactor projects. Hallucinations, stuck loops and other issues, can quickly run the infra bill up not to mention security.
I had Gemini ingest our huge aws cloudformation repo . I had it describe each infrastructure component and how it related to others and creation hierarchy and IAM.
I got a nice and comprehensive infrastructure requirement document out of this.
Now I am using it to create Terraform repo , deploying it via OpenTofu and comparing it to my existing AWS cloud formation . This part is still a WIP .
I have used ChatGPT to generate perfect IaaC using the CDK and Terraform. I give it my labelled descriptive design diagram that I have to do anyway.
I am very detailed about all of the security group requirements, tell it that I don’t need Internet access and tell it which VPC endpoints. I don’t do “agentic coding”.
Exactly. It's just so much cleaner to do it in the Cloud provider's native tooling. The impedance mismatch from Cloud-agnostic abstractions always just makes thing shitty enough that in the long run you spend more time dealing with weird edge cases.
Besides, actual full-scale Cloud migrations are exceedingly rare.
Terraform is not an abstraction on top of multiple cloud providers, you work with aws, azure etc explicitly. It is , however, agnostic in the sense that you can provision aws, azure, gcp, etc resources within the same iac project
I always hated this meme. Using Terraform no more makes you “cloud agnostic” than using Python to script AWS services and calling boto3 than using bash and calling the AWS CLI.
AWS's native tooling is Cloudformation, and CDK is actually just a wrapper around that that generates cloudformation code (as CDKTF is a wrapper for terraform). And I like to avoid cloudformation as much as possible.
writing HCL is so much more enjoyable than writing CF, even if HCL is fairly verbose (hey, it's not as bad as XML!). CF feels like a series of PM requirements dutifully codified with no dogfooding whereas HCL/TF feels like a tool that was developed by people who actually wanted to use it.
ARM cancelled their architecture license and sued them, Qualcomm won, but with a threat like that to your core business it's best to have an escape hatch.
They'll need to license future versions of the ARM ISA and now they know the licensor is hostile.
Go does surprisingly well at keeping GC freezes to a minimal in a way that you're unlikely to notice... C# has gotten a lot better since the core split as well. That said, there's a lot that comes down to how a developer creates a game.
I was added late to a project working on a training simulation engine, similar to games, where each avatar in the game was a separate thread... man, the GC pauses on the server would sometimes freeze for literally 10-15s, and it was not good at all. I refactored it to use an event-loop model and only 2 other threads, which ran much better overall. Even though it wasn't strictly a game itself, the techniques still matter. Funny how running through a list of a few hundred things is significantly better than a few hundred threads each with their own timers, etc.
> C# has gotten a lot better since the core split as well.
It has improved but the majority of games using C# are using Unity which does not use .NET (Core). It uses Mono or IL2CPP specifically with the Boehm GC so it performs significantly worse than .NET and even standalone Mono (SGen GC).
> Funny how running through a list of a few hundred things is significantly better than a few hundred threads each with their own timers, etc.
State machines are not in fashion. Exposed event loops are not in fashion. Most frameworks do their damnedest to hide those components.
As for GC freezes, if you're doing a game like project you can always just allocate a few huge arrays at startup and reuse those with no deallocation/allocation in most garbage collected environments.
It's not what people mean when they say GC though, especially in reference to games, where you care about your peak frame time more than about your average frame time.
Reference counting can also have very bursty performance. Consider what happens when you decrement the last reference to an object which is the sole remaining reference to an entire large tree of other objects. This will trigger a whole cascade of subsequent decrements and deallocations, which can be arbitrarily large.
Of course, you might say, "Well, sure, but your reference counting implementation doesn't need to eagerly deallocate on dereference." That's true! You can write a ref counter that defers some of those deallocations or amortizes them across multiple operations.
And when you do that, now you really do have a garbage collector.
You should watch some of the more recent Gamers Nexus videos... the average frame pacing counts for a lot, and they're making a concerted effort to show this, as it does represent the level of "jank" in games very well.
More broadly than frame pacing, https://www.youtube.com/watch?v=Fj-wZ_KGcsg is a recent example of one of _many_ interviews going back years on why both frame times and frame rates are all flawed for explaining why some games feel smoother/lag more than others (there are GN videos dating back to 2016 on the subject)
I haven't dug deep enough into C# to say this with certainty, but I believe later C# versions allows you to do enough manual allocation to "almost" get around the garbage collector. As well as new calls to try and nudge the GC away from hot paths.
You need to be very disciplined to pull this off, though. LINQ is basically off limits, for example. And of course, Godot's C# is likely much older than these modern techniques to begin with.
That's good to know. So it probably has the capability if you really wanted to dig in.
But that effort on an active engine would quite a long time to comb through. Really comes down to if a highly invested contributor wants to push it through and gets the go ahead.
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