SwellJoe
Joined 19 years ago
Joined 19 years ago
For years, Red Hat employed more kernel developers than anyone and contributed more. These days they're "only" the fourth largest contributor, after Intel, Google, and Meta, but they are still among the largest corporate contributors.
If that's a lean kernel org, I don't know what a fat one would look like.
The order of generosity, as it seems to be from my limited testing is currently Gemini->Claude->ChatGPT. (And, if we're including Chinese subscriptions, Kimi is below all of those. Very stingy.)
It's shitty for a new project to ride on the coattails of a trusted project with years of reputation. It misleads and confuses folks.
Take inspiration anywhere you like, borrow the code all you like, but don't steal the damned name.
This post explicitly says that's been improved in Carbon. So, here's hoping. Google currently has the most generous usage limits on their $20 plan among US providers, so it's a pretty good deal.
I'd be happy to be wrong, though. I've never tried to do biology with Claude, but I have gotten many refusals and downgrades for security work.
I think if I had to build an emergency LLM today, that had to run on modest hardware, I'd bet on Gemma 4 12B. It's got excellent reasoning and good vision/audio and speaks 140 languages.
But, I don't know about the "classic" knowledge base theory, though. Is there a high quality curated pile of survival information that could be bundled into a web UI and made searchable in a knowledge base? The LLMs aren't focused on that topic, so there's a lot of wasted space, but they know a little about a lot of things, including survival topics. Combined with Wikipedia, and maybe a few other sources, you're probably better off with one than without.
I guess one could use some huge models plus web search to compile/distill a focused survival knowledge base or LLM.
Edit: Project NOMAD seems to mostly be exactly that. It has authoritative sources in a searchable knowledge base and the tiny LLMs are an afterthought, which is probably what they should be. https://www.projectnomad.us/
The reality of launching a good product with AI is that the coding is very fast, but the QC, the documentation, the refinement and user testing, isn't all that much faster, if you care about it being good.
This is a mountain of code, full of bugs and weirdness that users will be the first to find, because nobody else is looking at it.
My process for building with AI is "intense weekend of vibe coding" and then several times that time spent on refinement and testing that comes from actually using the software a lot. A couple of devs can't be responsible for every major application.
With AI, you can make anything you want, but you can't make everything.
I work on Virtualmin. You can find it at http://www.virtualmin.com
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