tl;dr - AI researchers have never had to undergo code review, deal with continuous integration, or manage expectations of inexperienced users of their software.
Which is just far too true, and remains true outside of VC-backed scenarios like huggingface, but only because their playbook explicitly optimizes for this.
On the other hand, it’s a great time to be a seasoned software engineer who can help with these sorts of issues. If you’re trying to level up your machine learning experience - consider a strategy like this:
Pick a random lucidrains repository.
Try to get it running on your setup. It probably won’t. (No offense Phil! You’re doing God’s work and can’t cover every possible configuration).
Fix the issue.
Write a test for it.
Setup basic CI for the test.
Try to get the PR merged!
Which is just far too true, and remains true outside of VC-backed scenarios like huggingface, but only because their playbook explicitly optimizes for this.
On the other hand, it’s a great time to be a seasoned software engineer who can help with these sorts of issues. If you’re trying to level up your machine learning experience - consider a strategy like this:
Pick a random lucidrains repository. Try to get it running on your setup. It probably won’t. (No offense Phil! You’re doing God’s work and can’t cover every possible configuration). Fix the issue. Write a test for it. Setup basic CI for the test. Try to get the PR merged!