"China has overtaken the US in the global market for 'open' artificial intelligence models, gaining a crucial edge over how the powerful technology is used around the world."
I’ll be hanging out at our poster on membership inference, but in the same slot Brian Lester will present our work on “The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text” (poster 102)! [https://arxiv.org/abs/2506.05209]
1/2 We've heard of the curse of dimensionality. But what about the curse of multilinguality? "If you try to pack more languages into the same size model, they are each going to degrade," said @shaynelongpre.bsky.social of @mit.edu at the Simons Institute.
Beijing-backed technology gains ground as American giants hold fast to ‘closed’ AI strategies
Policymakers must recognize the open source AI ecosystem is where influence is being negotiated: not just which models exist, but which are used; not just who can train a trillion-parameter network, but who can make it deployable, modifiable, and relevant, say Lucie-Aimée Kaffee and Shayne Longpre.
Simons Institute for the Theory of Computing
A. Feder Cooper
To understand and shape the distribution of power in AI, look to the open source ecosystem, say Lucie-Aimée Kaffee and Shayne Longpre.
[NeurIPS '25] Really excited to present “Exploring the limits of strong membership inference attacks on large language models” (poster 1300) this morning (Friday December 5, 11am-2pm in Exhibit Hall C-E)! [https://arxiv.org/abs/2505.18773]
