David Siegel: Why We Must Actively Fund Open Source AI Now
Must actively fund open source AI [pdf]
After debating Richard Stallman on open source in the 1980s, I now see the same fight unfolding in AI. While frontier models become increasingly closed, we risk locking away the very knowledge driving scientific progress. Transparency is essential for safety and innovation, yet the code and data behind today's models are vanishing. We must actively fund open source AI to ensure it remains a public good rather than a proprietary oracle.
An openness that can be switched off at will is not a foundation; it is a favor.
- rao-v
We really need to band together to fund / sponsor targeted inducement prizes (a la Nobel laureate Michael Kremer) for open models.
Every 6-12 months, give out $200K to the first model to hit a min threshold on a set of ~5-10 hard benchmarks (+ perhaps one secret benchmark) using a total of 16GB / 32GB / 64GB / 128GB of VRAM (at a min context length of 200K), then move the threshold up. Quantization etc. is dealers choice, it just needs to nail the benchmark on a reference machine by using exactly that much VRAM (no mapping to RAM / disk etc.)
You could crowdsource the funding, and cross subsidize by adding targeted prizes focused on corporate needs (the classic one is PDF processing benchmarks), and say that 25% of each corporate prize funding also flows into the general prize pool.
For a lot of these open-source model companies, it's less about the $s (though $200K is nothing to sneeze at), it's the clear recognition that helps their model efforts stand out, gain usage etc.
- theplumber
The private AI companies should be forced to release the models as open weights with a license (I.e no commercial use) due the high risk they present and the data they basically steal from everyone to train their models.
This should be the safety push not the regulatory capture that Dario is trying.
- thatguymike
FOSS is the wrong analogy. Building frontier LLMs isn’t primarily an engineering discipline, it’s a scientific research program.
Of course we do have basically open source research programs, including most universities and big projects like CERN. But AI grew up in universities until it transpired that sufficient capital could only be found in the private sector.
It would be possible to make a decent publicly funded AI research program. But it would look more like the Manhattan or Apollo projects (which frontier labs already model themselves after) than some extra research grants for universities.
- hereme888
They already invest in open-source AI, but nothing is truly free. Commercial AI will usually dominate because devs are paid to make it their primary effort. Goodwill and part-time contributions cannot reliably compete with livelihood and profit incentives.
- djolo2211
Just because a software is closed-source doesn't mean the knowledge can't be shared. You don't need to see the underlying code to explain to someone architectural patterns or best practices.
The library analogy in the scenario would hold true if LLM providers refused to answer any questions about RL or Transformers.
I am a big proponent of open-source open-weight models, but mostly because I think it's just a better product. We've seen that they are much cheaper to train and operate. Frontier intelligence might not be needed for most tasks. Just let the market decide. My bet is that LLMs will become analogous to programming languages, and big labs will make their money by fine-tuning models for very specific use cases or by deploying them for customers.
- ChrisArchitect
Title was: I argued with the father of open source for 2 years. Now the AI fight is the same — only bigger
Op-ed alt link: https://fortune.com/2026/07/03/open-source-ai-same-fight-as-...
- brandonJagger
“The economists need to start charting this out, if we are in a post scarcity world, how does everyone benefit from that?, obviously its not correct for just a few people or a few companies or even a few nations to be benefiting from this technology, it has to broadly accrue the benefits to everyone, but how is that gonna be done? We really need answers now. ” -Demmis Hassabis <Google Deep mind>
- JohnLinotte
The sovereignty point resonates. The June 2026 export controls
on Anthropic's models were a wake-up call.
Open weights + deterministic orchestration feels like the only
sane long-term bet.