That’s an interesting point, and leads to a reasonable argument that if an AI is trained on a given open source codebase, developers should have free access to use that AI to improve said codebase. I wonder whether future license models might include such clauses.
I would use it for contributions to open source projects but I do not pay for any AI subscriptions, and I can’t use my employee account for copilot enterprise for non-work projects.
Every week for the last year or so I have been testing various copilot models against customer reported software defects and it’s seriously at a point now where with a single prompt Gemini pro 2.5 is solving the entire defect with unit tests. Some need no changes in review and are good to go.
As an open source maintainer of a large project I have noticed a huge uptick in PRs which has created a larger review workload, I’m almost certain these are due to LLMs. Quality of a typical PR has not decreased since LLMs have become available and I am thus far very glad
If I were to speculate I’d guess the huge increase in context windows has made the tools viable, models like GPT5 are garbage on any sizable code bases
Oh good. They can show us how it’s done by patching open-source projects for example. Right? That way we will see that they are not full of shit.
Where are the patches? They have trained on millions of open-source projects after all. It should be easy. Show us.
That’s an interesting point, and leads to a reasonable argument that if an AI is trained on a given open source codebase, developers should have free access to use that AI to improve said codebase. I wonder whether future license models might include such clauses.
Free access to the model is one thing but free access to compute for it is another
Are you going to spend your tokens on open source projects? Show us how generous you are.
I’m not the one trying to prove anything, and I think it’s all bullshit. I’m waiting for your proof though. Even with a free open-source black box.
What’s a free open source black box?
Some kind of bad joke that went way over your head. Where are your merge requests?
At work, the software is not open source.
I would use it for contributions to open source projects but I do not pay for any AI subscriptions, and I can’t use my employee account for copilot enterprise for non-work projects.
Every week for the last year or so I have been testing various copilot models against customer reported software defects and it’s seriously at a point now where with a single prompt Gemini pro 2.5 is solving the entire defect with unit tests. Some need no changes in review and are good to go.
As an open source maintainer of a large project I have noticed a huge uptick in PRs which has created a larger review workload, I’m almost certain these are due to LLMs. Quality of a typical PR has not decreased since LLMs have become available and I am thus far very glad
If I were to speculate I’d guess the huge increase in context windows has made the tools viable, models like GPT5 are garbage on any sizable code bases