Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other ‘AI’ tools will no longer be welcome. This follows on the heels of a similar ban on cryptocurrency-related projects.

The community vote was on two issues, the first being the notion that scraping of project code for the use in LLMs should be forbidden, which was a motion that easily passed. The second motion was on disallowing projects whose code was substantially generated by LLMs like Claude, OpenAI Codex, and similar. This motion passed with 358 in favor versus 144 against.

In the earlier linked blog post the reasoning behind especially this second issue is expanded upon, covering not only ‘license whitewashing’, but also the direct and indirect hardware costs, with the expanding ‘AI’ datacenter hyperscaling having massively increased hardware costs for Codeberg over the past years, as the costs have been largely externalized.

Also covered is also the aspect of these LLM-based tools destroying the OSS community, which is something that is backed up by recent studies. Even if we ignore that such LLM-tools are destroying the cognitive abilities of its users, there’s an argument to be made that if LLM-scraping is disallowed, then it’s consistent to also not allow LLM-generated code.

In the Terms of Use you can see these changes, both for LLMs and for cryptocurrency projects.

Thanks to [mk-fg] for the tip.

Oh, the farming lifestyle…living off the land, fending for yourself. But who’s got time for all that? For the modern hacker, the best option in the garden space may be this over-engineered automated AI tomato farm created by [Gerd Nicolay]. You can even interact with it right now through the magic of the Internet.

[Gerd] started off with your run-of-the-mill pot and plant, choosing the humble tomato to keep the system simple. Then things started to escalate, with the addition of automatic lighting, watering, and data logging environmental parameters like humidity. Now we’re getting somewhere, but there’s more that can be added. How about an entire AI council to monitor and decide the fate of each individual tomato while recording an entire storyline to go alongside the growing cycle?

That’s right, four different models collaborate to ensure only the utmost quality of care for these tomatoes based on camera feeds, humidity, and various other environmental factors being recorded constantly. Is this a little overkill? Maybe for those who have even a modest sense of gardening knowledge — but who can bash the mountain of documentation and data collection on these wonderful little plants?

Perhaps the best part: you can recommend actions for the AI counsel to take from the comfort of your own web browser. While the TomatoFarm might be slightly unnecessary for the average farmer, if you want to try a more reasonable monitoring system, we have you covered too!