I do find using AI in a clean-room reverse-engineering project amounts to shooting yourself in the foot: you're sleep-walking into a legal minefield in an already legally gray field, and also risk over-relying on the AI's trial-and-error instead of developing a solid intuition of its functioning yourself.
At the same time, if we're being honest, Synaptics will have sent the C&D no matter what. They are an anti-consumer company with more lawyers than engineers, so of course they'll use all their resources to bully any competition, especially the most vulnerable.
Clean-room reverse engineering involves two teams: one with access to the thing being reverse engineered, who write documentation of it, and the one in the clean room who do the implementation based only on the documentation. There's no reason you could not use AI for the first part, as the documentation is then evidence that you are only looking at behaviour and not source code.
Using it inside the clean room is more of an issue.
If you use have the first team use one provider to write the spec and a completely different provider for the implementation team, I would expect you would be covered, but it probably will take the first players in this game to establish that precedent by having their cases tried in court.
I just checked and there are some forks around you could salvage the original work from. I won’t post the links but I’m sure those motivated enough can find them.
This is an utterly confusing and self sabotaging system. I had lots of issues with displaylink on a Mac. (Daily crash on the first video call of the day for some reason) Does the support care? No. Can I debug using the logs? No - THEY'RE ENCRYPTED! And now they're fighting for customers to not be able to use the hardware.
Save yourself time and money - avoid DisplayLink.
At least part of the effort was posted in mailing list though https://lwn.net/Articles/1078474/ - I hope the recent repository has been mirrored too.
> In addition, as I have previously made clear to you, by open sourcing our proprietary DisplayLink technology for whatever personal reasons you may have as a "hobbyist," you would be single-handedly eviscerating DisplayLink's competitive advantage in this crowded market by educating our competitors and other third parties as to how we implement our market-leading proprietary technology. We have gone to great lengths and great expense to prevent such disclosures and protect our market space. Your actions are potentially putting tens of millions of dollars of yearly corporate revenue at risk.
> In short, by your ongoing actions, you are effectively making a significant, dramatic, and grave business decision on behalf of Synaptics and DisplayLink that you have absolutely no authority to make. Given the magnitude of the potential damages at stake, we cannot and will not let this happen. We demand your immediate cessation of your infringing activities, and we will continue to escalate this matter through every available legal channel if you fail to comply.
> That "Vino" driver for DisplayLink driver was a clean-room reverse-engineered DisplayLink driver that was developed in part by AI and written in Rust.
It is my strongly-held opinion that, regardless of what you think about AI in general, reverse engineering projects ought to stay as far away as possible from LLM code gen as possible. They are a very easy and straightforward way for a copyright owner to claim access to their code, since basically ALL code was trained on. Unless you have hard evidence the particular bit of code you want to RE was not in the training set, you should not use an LLM to reverse-engineer or rewrite it.
This is not a moral argument; as much as I hate AI companies playing fast and loose with other people's work, the underlying arguments that make RE legal work much better if you do not look at the source code. And while US judges are straining to keep AI training fair use, that does not make the AI a copyright laundering device. A copyright owner can absolutely reach through a fair use to get to you. Think of it like if you downloaded 10 different YouTube video essays on the same movie and attempted to stitch them together into a normal copy of the underlying movie. Obviously, your use has a different (and worse) legal status than the reviews do.
With typical clean room RE you get two artificers with clean copyrightbility - a fair use spec describing the system, a new implementation. This is not legally required, but the paper trail is a good defense.
If AI writes the spec, it may have just tainted itself if that work is then used to in future training. The output is not protected by copyright, but that probably doesn’t matter. If AI writes the output, there is no protection over that either, which may or may not matter.
Ultimately, however, this is a mechanical, derivative work. It isn’t washed because no creative human expression was introduced in either phase.
If the phases are split into AI writing the spec and human writing the implementation, and the spec is determined to be infringing, the implementation is infringing. The AI spec has no judgement over what’s copyrightable expression in the original, and there’s a high likelihood it produces an unauthorized derivative.
If a human writes the spec and an AI writes the code, the output is probably clean, but also not copyrightable. This is less of a concern for open source projects written by a single maintainer, but may have effects for larger projects or proprietary projects. However, writing the spec is the harder of the two parts and what people like using AI for.
Mostly agree. It's been super helpful for personal use but I don't think it's possible to achieve a true "clean room" implementation. Anything copyright encumbered should stay away.
On the other hand, it's been great for poking at cheap IoT devices and figuring out how to interact without crappy proprietary apps.
At the same time, if we're being honest, Synaptics will have sent the C&D no matter what. They are an anti-consumer company with more lawyers than engineers, so of course they'll use all their resources to bully any competition, especially the most vulnerable.
Using it inside the clean room is more of an issue.
Thousands of developers are going to do this now.
Frankly all RE and emulation projects should at least have a mirror there.
Save yourself time and money - avoid DisplayLink.
At least part of the effort was posted in mailing list though https://lwn.net/Articles/1078474/ - I hope the recent repository has been mirrored too.
There's also https://github.com/durhamaustin9/DisplayLink-Drivers-Reconst... you may want to preserve locally.
> In addition, as I have previously made clear to you, by open sourcing our proprietary DisplayLink technology for whatever personal reasons you may have as a "hobbyist," you would be single-handedly eviscerating DisplayLink's competitive advantage in this crowded market by educating our competitors and other third parties as to how we implement our market-leading proprietary technology. We have gone to great lengths and great expense to prevent such disclosures and protect our market space. Your actions are potentially putting tens of millions of dollars of yearly corporate revenue at risk.
> In short, by your ongoing actions, you are effectively making a significant, dramatic, and grave business decision on behalf of Synaptics and DisplayLink that you have absolutely no authority to make. Given the magnitude of the potential damages at stake, we cannot and will not let this happen. We demand your immediate cessation of your infringing activities, and we will continue to escalate this matter through every available legal channel if you fail to comply.
Now there are going to be hundreds of clones.
It is my strongly-held opinion that, regardless of what you think about AI in general, reverse engineering projects ought to stay as far away as possible from LLM code gen as possible. They are a very easy and straightforward way for a copyright owner to claim access to their code, since basically ALL code was trained on. Unless you have hard evidence the particular bit of code you want to RE was not in the training set, you should not use an LLM to reverse-engineer or rewrite it.
This is not a moral argument; as much as I hate AI companies playing fast and loose with other people's work, the underlying arguments that make RE legal work much better if you do not look at the source code. And while US judges are straining to keep AI training fair use, that does not make the AI a copyright laundering device. A copyright owner can absolutely reach through a fair use to get to you. Think of it like if you downloaded 10 different YouTube video essays on the same movie and attempted to stitch them together into a normal copy of the underlying movie. Obviously, your use has a different (and worse) legal status than the reviews do.
Also, fuck Synaptics.
With typical clean room RE you get two artificers with clean copyrightbility - a fair use spec describing the system, a new implementation. This is not legally required, but the paper trail is a good defense.
If AI writes the spec, it may have just tainted itself if that work is then used to in future training. The output is not protected by copyright, but that probably doesn’t matter. If AI writes the output, there is no protection over that either, which may or may not matter.
Ultimately, however, this is a mechanical, derivative work. It isn’t washed because no creative human expression was introduced in either phase.
If the phases are split into AI writing the spec and human writing the implementation, and the spec is determined to be infringing, the implementation is infringing. The AI spec has no judgement over what’s copyrightable expression in the original, and there’s a high likelihood it produces an unauthorized derivative.
If a human writes the spec and an AI writes the code, the output is probably clean, but also not copyrightable. This is less of a concern for open source projects written by a single maintainer, but may have effects for larger projects or proprietary projects. However, writing the spec is the harder of the two parts and what people like using AI for.
On the other hand, it's been great for poking at cheap IoT devices and figuring out how to interact without crappy proprietary apps.