251–260 of 951 posts
Not who I would've liked to acquire Astral. As long as OpenAI doesn't force bad decisions on to Astral too hard, I'm very happy for the Astral team. They've been making some of the best Python tooling that has made the ecosystem so much better IME.
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> If you don't want your lunch eaten by a private equity firm, make sure whatever tool you use is GPL licensed. 1. For the record: the GPL is entirely dependent on copyright. 2. If AI "clean-room" re-implementations are allow to bypass copyright/licenses, the GPL won't protect you.
Maybe I'm reading wrong here, but what's the implication of the clean room re-implementations? Someone else is cloning with a changed license, but if I'm still on the GPL licensed tool, how am I "not protected"?
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It's not any different from the launch of the FSF. There's a simple solution. If you don't want your lunch eaten by a private equity firm, make sure whatever tool you use is GPL licensed.
The biggest scam the mega-clouds and the Githubs ever pulled was convincing open source developers that the GPL was somehow out of vogue and BSD/MIT/Apache was better. All so they could just vacuum it all up and resell it with impunity.
Feel free to prove me wrong by pointing out this massive amount of advocacy from "mega-clouds" that changed people's minds.
The ads, the mailing list posts, social media comments. Anything at all you can trace to "mega-clouds" execs.
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It's not any different from the launch of the FSF. There's a simple solution. If you don't want your lunch eaten by a private equity firm, make sure whatever tool you use is GPL licensed.
The biggest scam the mega-clouds and the Githubs ever pulled was convincing open source developers that the GPL was somehow out of vogue and BSD/MIT/Apache was better. All so they could just vacuum it all up and resell it with impunity.
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They raised 4M USD, they have 26 full-time employees (they pay 120 200K / yr, cf https://pitchbook.com/profiles/company/523411-93 ). It means the company almost reached their runway, so all these employees would have to find a job. It's a very very good product, but it is open-source and Apache / MIT, so difficult to defend from anyone just clicking on fork. Especially a large company like OpenAI who has massive dist…
A brief note, your numbers are way off here — Astral subsequently raised a Series A and B (as mentioned in the blog post) but did not announce them. We were doing great financially. (I work at Astral)
I would sincerely have understood better (and even wished) if OpenAI made you a very generous offer to you personally as an individual contributor than choose a strategy where the main winners are the VCs of the purchased company.
Here, outside, we perceive zero to almost no revenues (no pricing ? no contact us ? maybe some consulting ?) and millions burned.
Whether it is 4 or 8 or 15M burned, no idea.
Who's going to fill that hole, and when ? (especially since PE funds have 5 years timeline, and company is from 2021).
The end product is nice, but as an investor, being nice is not enough, so they must have deeper motives.
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The biggest scam the mega-clouds and the Githubs ever pulled was convincing open source developers that the GPL was somehow out of vogue and BSD/MIT/Apache was better. All so they could just vacuum it all up and resell it with impunity.
I remember a somewhat prominent dev in the DC area putting on Twitter around 2012 or so something like "I do plenty of open source coding and I don't put a fucking license on it" and it stuck with me for all these years that it was a weird stance to take.
Not who I would've liked to acquire Astral. As long as OpenAI doesn't force bad decisions on to Astral too hard, I'm very happy for the Astral team. They've been making some of the best Python tooling that has made the ecosystem so much better IME.
If Codex’s core quality is anything to go by, it’s time to create a community fork of UV
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If LLMs turn out to be such a force multiplier, the way to fight it is to ensure that there are open source LLMs.
I think the issue is that LLMs are a cash problem as much as they are a technical problem. Consumer hardware architectures are still pretty unfriendly to running models which are actually competitive to useful models so if you want to even do inference on a model that's going to reliably give you decent results you're basically in enterprise territory. Unless you want to do it really slowly. The issue that I see is t…
Company that repeatedly tells you software developers are obsoleted by their product buys more software developers instead of using said product to create software. Hmm.