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The tweet highlights the impressive naming conventions of American open-source AI models in 2026, listing examples such as Nemotron, Laguna, Trinity, Inkling, and Glimmer.
Microsoft publishes a policy essay arguing that open-weight AI models are critical to American AI leadership, competition, and broad economic diffusion, while acknowledging their risks.
An op-ed and Bitcoin Policy Institute reports allege that foreign money, including from a Shanghai-based donor, is funding grassroots opposition to American AI data centers, resulting in billions in delayed investment. The article details coordinated campaigns in the Bay Area and beyond aimed at slowing the U.S. AI buildout.
NVIDIA published a white paper discussing the role of open-weight AI models in maintaining American AI leadership.
Lucas Atkins of Arcee AI announces the GS1 model and discusses the need for American open-model alternatives to Chinese AI models, expressing optimism about the ecosystem.
The article questions why American open-source AI labs have not achieved top benchmark results like their Chinese counterparts, highlighting a perceived gap in open-source AI development between the two nations.
A tweet discusses the need for an American equivalent of DeepSeek, with Anthony Pompliano advocating for open source AI models from the US to become the default quickly.
Hugging Face CEO Clement Delangue criticizes tech leaders like Palantir's Alex Karp for advocating American open-source AI models without contributing open-source models or datasets themselves.