This podcast episode covers recent AI news: the release of Nemotron 3 Super, an open hybrid Mamba-Transformer MoE model; the departure of another xAI cofounder; and Anthropic's lawsuit against the U.S. Department of Defense.
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Nvidia releases a 120B-parameter open-source model, Nemotron 3 Super, featuring a hybrid Mamba-Transformer architecture and native 4-bit training, optimized for Blackwell GPUs and designed to enhance agentic reasoning.
Nvidia has released Nemotron 3 Super, a 120B-parameter open-source model employing a hybrid Transformer-Mamba architecture with latent-MoE. The model is trained natively at 4-bit precision and designed for Blackwell GPUs. Nvidia's official technical blog describes it as "an open hybrid Mamba-Transformer MoE for agentic reasoning."
Concurrent with the model release, Nvidia halted H200 production in China due to customs blockades and domestic chip competition pressure. This decision reflects the ongoing impact of geopolitics on the AI hardware supply chain. Additionally, xAI experienced a wave of co-founder departures, Anthropic previewed Claude Marketplace for enterprise procurement, Yann LeCun's aMI raised $1.3 billion, and humanoid robot company Sanctuary reached a valuation of $1.15 billion.
Anthropic sued the U.S. Department of Defense for listing Anthropic as a "supply chain risk," with an internal memo requiring military commanders to remove Anthropic AI technology within 180 days. Google and OpenAI filed legal briefs supporting Anthropic. Meanwhile, research revealed issues such as model resistance to activation steering, limitations in chain-of-thought control, and low-probability risky behaviors.
Information sourced from Last Week in AI podcast episode 237, which summarizes and discusses weekly AI news based on multiple media reports (The Verge, TechCrunch, NVIDIA Technical Blog, etc.), constituting a secondary composite source. Specific figures and conclusions should be verified against original reports.
Nvidia Nemotron 3 Super represents innovation in open-source model architecture and training methods, but geopolitical factors are profoundly affecting the AI hardware market, while legal disputes and model safety research also advance in parallel.
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