[demosthanos]

Yes, the problem with comparing open models to open source is that open source requires humans to volunteer their time. Open models requires humans to volunteer their money.

These two types of contributions have very different behavioral profiles, and it doesn't obviously follow that the historical success of getting people to collaborate socially on building software for fun and for the benefit of the community will translate in any meaningful way to the necessity of being able to raise enormous amounts of money to pay for enormous amounts of electricity.

[enos_feedler]

The biggest hurdle is whether humans volunteer their expertise. Not time or money. We need top talent to make the open models. Sponsorship is plentiful. Open source volunteers are less critical with LLM doing the grunt work. Its about talent contributing to the open

[calebkaiser]

This is not my experience working in the field the last 8 years. There is not a dearth of talented researchers, engineers, etc. who are willing to contribute to open models. Just look at the ecosystem generally, from academia to industry. So much research still happens in the open, and the open source community in ML is still massive and energetic.

Training a new frontier model just costs a lot of money and there are very few companies for whom it makes sense to do so, and even fewer orgs who are just going to gift those kinds of resources to an open source initiative.

[hobofan]

> open source requires humans to volunteer their time

Your idealistic of open source may require that, but in practice a huge part of open source is commercial and a large chunk of that is low on collaboration (across vendor boundaries).

[connicpu]

Technically open source requires some amount of monetary volunteering, it's just that the electricity to run a code editor and compile (most) open source code bases is within hobby budget for most people.