In December 2025, President Trump held a private meeting with Elon Musk and spent hours interacting with Musk’s Grok chatbot, asking how Venezuelans would respond if their president, Nicolás Maduro, were captured. Grok told him Maduro was a “deeply unpopular dictator” and predicted many Venezuelans would celebrate his downfall; similar celebrations followed after U.S. forces invaded Venezuela and captured Maduro on January 3. The encounter came months after Trump began ordering strikes on Venezuelan boats in September and about seven months after Musk left a White House role at the Department of Government Efficiency. Trump took away an impression that Grok’s analysis was ingenious.
The piece also documents growing military reliance on Musk’s models: in June the Pentagon’s head of AI said the military used Grok Gov to help deploy and strike targets during the Iran War, and Grok is now among several AI systems (alongside OpenAI’s and Anthropic’s offerings) engaged by the Department of Defense. The Pentagon recently tapped Musk and Anduril co-founder Palmer Luckey to co-lead a study on how advanced technologies should be used on battlefields, highlighting the expanding influence of commercial AI chatbots in national-security decision-making.
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Shrivu Shankar argues that SaaS companies are evolving into 'harnesses,' where core tasks are performed by AI agents rather than humans. This shift transforms organizational structure, with humans overseeing and reviewing AI-driven processes within the company. (blog.sshh.io)
Three AI agents - Meta’s Muse, Anthropic’s Claude, and OpenAI’s GPT - were tested on multilingual research tasks involving U.S. and Iranian data. The experiment focused on how language and context influence agent performance across reasoning, sourcing, and artifact creation. (royapakzad.substack.com)
An open-source project named LDRAW-NOVA allows users to generate Lego models using AI. The repository contains tools, examples, and documentation for creating Lego designs with artificial intelligence. (github.com)
DwarfStar 4 (ds4) is a local inference engine that runs large language and vision models on high-memory Mac, CUDA, and ROCm machines. It supports models like DeepSeek V4 and Qwen3.8, offering CLI, APIs, and persistent cache features for efficient local deployment. (dwarfstar.sh)
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