He also mentioned it took 2 months. I’m actually wondering how long it would take to do the Linux to BSD port by eyeball, or at least ai assisted. Probably not that much longer? I guess it depends on wall time vs real time.

- have AI write a windows filter driver to capture all hardware communications

- have AI reverse engineer Windows WiFi driver and make a crude prototype

- have AI compare registers captured by filter driver with linux driver version and iterate until they match (or at least functional tests pass)

not exactly rocket surgery, and windows device drivers generally don't have DRM/obfuscation, so reverse engineering them isn't hard for LLMs.

Trial and error?

Just like it does when given an existing GPL’d source and dealing with its hallucinations, the agent could be operated on a black box (or a binary Windows driver and a disassembly)?

The GPL code helped here but as long as the agent can run in a loop and test its work against a piece of hardware, I don’t see why it couldn’t do the same without any code given enough time?

The Linux driver in this case is ISC licensed. There’s no legal or ethical problem in porting it. This is open source working as intended.

I feel like the jury is still out on whether this is acceptable for GPL code. Suppose you get agent 1 to make a clear and detailed specification from reading copyrighted code (or from reverse engineering). Then get agent 2 to implement a new driver using the specification. Is there anything wrong with that?

Combine AI + genetic algo?

https://www.reddit.com/r/learnmachinelearning/comments/1665d...

True. But also -- how do humans do it? There are docs and there's other similar driver code. I wouldn't be surprised if Claude could build new driver code sight-unseen, given the appropriate resources

GPL is not a patent. It covers the work and _derivatives_; it does not cover ideas or general knowledge. The chip in question has docs.

I fully expect that Claude wrote code that does not resemble that of the driver in the Linux tree. TFA is taking on some liability if it turns out that the code Claude wrote does largely resemble GPL'ed code, but if TFA is not comfortable with the code written by Claude not resembling existing GPL'ed code then they can just post their prompts and everyone who needs this driver can go through the process of getting Claude to code it.

In court TFA would be a defendant, so TFA needs to be sure enough that the code in question does not resemble GPL'ed code. Here in the court of public opinion I'd say that claims of GPL violation need to be backed up by a serious similarity analysis.

Prompts cannot possibly be considered derivatives of the GPL'ed code that Claude might mimic.

Repurposing NDIS drivers is a time honored tradition. No source, but oh well.

It could be given reference material like documentation/datasheets and/or just be prompted as to how it should work.

I haven't read the article but my first question was, install wifibox?

It's a bhyve VM running alpine Linux and you pass through your WiFi adaptor and get a bridge out on the freebsd host.

> What is interesting is it seems like the work resembles regular management, asking for a written specification, proof reading, etc.

That's how I've been using the bot for years. Organize tasks, mediate between them, look for obvious-to-me problems and traps as things progress, and provide corrections where that seems useful.

It differs from regular management, I think, in that the sunk costs are never very significant.

Find a design issue that requires throwing out big chunks of work? No problem: Just change that part of the spec and run through the process for that and the stuff beneath it again. These parts cost approximately nothing to produce the first time through, and they'll still cost approximately nothing to produce the second time.

I'm not building a physical structure here, nor am I paying salaries or waiting days or weeks to refactor: If the foundation is wrong, then just nuke it and start over fresh. Clean slates are cheap.

(I don't know if that's the right way to do it, or the wrong way. But it works -- for me, at least, with the things I want to get done with a computer.)

To make these things work you do need to write a spec and figure out what unit tests will prove it actually did what you want. Even then it will take a bunch of shortcuts so it's best if you're a domain expert anyway.

Aka, the hard part.

What would the GPL have to do with this?

I do not know why people do not just add GPL license to their generated code.

> We're very close to just being about to set an AI coding agent to brute-force a driver for anything.

This is false. To "brute force" a driver, you'd need a feedback loop between the hardware's output and the driver's input.

While, in theory, this is possible for some analog-digital traducers (e.g WI-FI radio), if the hardware is a human-interface system (joystick, monitor, mouse, speaker, etc.) you literally need a "human in the loop" to provide feedback.

Additionally, many edge-cases in driving hardware can irrevocably destroy it and even a domain-specific agent wouldn't have any physics context for the underlying risks.

I'm not so sure that Nouveau is slower than the proprietary Nvidia driver. I didn't run benchmarks on my personal use case but my subjective experience is that Nouveau might be faster. It's a Debian 11, X11, NVIDIA driver vs Debian 13, X11, Nouveau on the same laptop with a Quadro K1100mq. The desktop of the newer system seems to be faster. Of course it could be the sum of the individual improvements of kernel, GNOME, etc. I only move windows around my desktop, no games, so it's a very limited scenario.

someone would have already have replaced those closed source Nvidia drivers that have firmware blobs

This isn’t quite a fair example, these are so massively complex with code path built explicitly for so many individual applications. Nvidia cards are nearly a complete SoC.

Though then again, coding agents 1 year ago of the full autonomous sort were barely months old, and now here we are in one year. So, maybe soon this could be realistic? Hard to say. Even if code agents can do it, it still costs $ via tokens and api calls. But a year ago it would have cost me at least a few dollars and a lot more time to do things I get done now in a prompt and 10 minutes of Opus in a sandbox.

I've found ai really good at the rare problems. The code hangs 1 out of 200 times - it spends half an hour and finds a race condition and a proposed fix - something complex that is really difficult for humans to figure out. Now grated the above problem took a dozen rounds over a couple days to completly solve (and it happend more often than every two weeks), but it was able to find an answer given symptoms.

I've thought for a while now that we'll end up moving to stricter languages that have safer concurrency, etc, partly for this reason. The most prominent resistance against such languages was the learning curve, but humans like OP aren't looking at the code now.

So are people