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I sometimes get these almost angry emails about Gensim, my open source library. How come I'm not responding faster, merging PRs, fixing issues? For this critical popular project??!

Meanwhile, sponsorships are at 13% of the (not terribly ambitious) goal of $6k/month [0].

Yeah, that's why.

[0] https://github.com/sponsors/piskvorky




> How come I'm not responding faster, merging PRs, fixing issues? For this critical popular project??!

> Meanwhile, sponsorships are at 13% of the (not terribly ambitious) goal of $6k/month

The answer would then be: "because I have to keep another job to pay the bills" then? Hope you can get to your goal ASAP. Going by stupidly quick math, you have 12k stars for gesim alone, and that boils down that if every star on github payed 50 cents you'd already be there. I know that starring doesn't mean anything other than "hey, this looks interesting!", but then again 50 cents is probably cheap enough for a majority of those "stars" that they wouldn't even notice.

Also: thanks for creating and maintaining gensim!


Do you ever respond to these emails telling them that they can hire you to attend to their issue? If my business depended heavily on an open-source component that needed a bug fix, more often than not I would pay the person to spend their time to resolve it.

Often it is easier to get a business to pay a consulting fee for a specific thing rather than make a donation that goes into a general funding pool for a project.


Yes, I do. But it turns out that their issue is pretty much always only tangentially related to Gensim (or any other open source library / technology). They're solving a business problem. That's what brings them money, with which they pay me, and I acknowledge that.

This leaves me with two choices:

1. Help narrowly, with the Gensim part only. Pros: easy for me. Cons: doesn't truly help the customer; feels dirty.

2. Help solve their actual business problem. Even if it means not using ML at all (a very common outcome), or suggesting a different architecture.

In my experience, most companies are so lost as to what to expect from ML, or how to get there, that I didn't feel comfortable with the "narrow" help. Lipstick on a pig.

So I went the full consulting route for a few years. But that felt too draining so I dropped it and created a product instead.


But that triggers different accounting/taxes paths that can be problematic. Not everybody is a freelancer.


Thanks for creating Gensim!




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