What does open source maintenance actually look like once a project starts to scale? In this Open Source Friday stream, Ayushman Bhattacharya shares how Pollinations.ai built the systems behind a fast-growing open source AI project. We’ll dig into contributor workflows, paid quests, AI-assisted PR review, app submission pipelines, model curation, and what maintainers really spend their day doing.
Open Source Friday: Building the Contributor Pipeline at Pollinations.ai
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GitHub, if any engineer sees this, please help escalate ticket #4530577. It’s been several days with no response, and my account issue has disrupted my open source work overnight. I’d truly appreciate any help. 🙏
so using swarms of bots, thats dangerous
visit My distro Ai https://github.com/Codigo-Free/HarnessOS
Ai {RoboCop something}. Robot boos. That operation on android. Iphone and apple ,Mac inthoch , my idea. And bonus.give me.and my public.on the state.
what types of cognition loops are you using?
the thing is when you place simething on github bigtech will dissect your code based and concepts and adapt them into their systems and you don't get any recognition, ai will train on it and remove your license.
using HarnessOS
Very interesting, the issue with Open Source AI is mainly the lack of processing power but it can be applied in embedded systems where there's no connectivity. Curious: In your workplace, do you use Private AIs like Claude or Open Source Models? Which one fits to your needs?
The more successful your open source project is. The more you have to deal with bots overwelming your betting process with bogus pushes. In this case the FreeBSD model to open source is superior. Anyone can get the code. But only people with credentials can contribute to it. Pull the bot trick and you get banned from contributing. And since AI can copy entire codebases and "create something new" (which is BS as is derivative), the license becomes moot.