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.
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.
> 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.
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.
If they were smart, they'd welcome an effort to make DisplayLink not a piece of trash.
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.
I hope someone has archived the repository so it can be hosted somewhere where those ridiculous Western copyright and patent laws don't apply.
Should have hosted it on Radicle, with the main node served over Tor.
Frankly all RE and emulation projects should at least have a mirror there.
Can't wait til there's a good alternative. Displaylink is such a pain
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.
There's also https://github.com/durhamaustin9/DisplayLink-Drivers-Reconst... you may want to preserve locally.
> 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.
Also, fuck Synaptics.
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.