Open Season

Supporting widely available AI models can coexist with favoring temporary release restrictions. The Open Season essay reads Meta's vision of distributed AI power as closer to other frontier labs' immediate precautions than its broad rhetoric suggests.

The essay's reasoning turns on timing. Distributing capability could prevent power from concentrating in a few organizations, while institutions may need time to prepare for that capability. Those positions can lead to overlapping proposals for testing models and strengthening infrastructure before broader release. In the author's reading, the near-term steps Mark Zuckerberg proposes resemble what other labs already do, so the visible difference between the camps lies mostly in their long-term framing.

“Muse Glimmer is an open-weight 30B parameter multimodal model . It seems to perform better than the Gemma 4 31B model, and roughly the same as Qwen3.6 27B.”

MTS

“The conventional view is that these concerns are about technology, and that if we take enough time, then we can perfect or align the technology to produce a single benevolent superintelligence. I think this view of alignment is fundamentally flawed.”

MTS

“AI is moving very quickly. And not only is progress in the capabilities of the models themselves happening quickly, the diffusion of the technology into society and the economy is also moving very fast.”

MTS

“Institutions are made up of people, and people take time to react. In the long run, the checks and balances may arrive, and a balance of power may assert itself. But there may also be a moment where the capabilities are here and the institutions are out to lunch.”

MTS

“I propose that companies developing frontier AI should commit significant technical resources towards helping the government harden critical infrastructure. I also propose that frontier AI labs should share intermediate training checkpoints of new models for government use and review rather than waiting until training has completed.”

MTS