Warning, this post is going to be about one of the most boring topics possible, font choice. The Washington Post reports the State Department has ordered a shift in font choice from Times New Roman…

Notwithstanding pronouncements from leading officials of the Trump administration, the consensus of federal courts is that the Constitution protects the right to record immigration raids, and federal ...

Large language models can have billions, or even trillions, of parameters. But how big do they need to be to achieve acceptable performance? To test this, I experimented with several of Google's Gemma 3 models, all small enough to run locally on a single GPU. Specifically I used the 1 billion parameter model, the 4 billion parameter model, and the 12 billion parameter model.

Large Language Model AIs like Google's Gemini and Open-AI's GPT can be interesting to play around with even in a simple chatbot like Chat-GPT. But those chatbots largely waste their potential. Their understanding of natural language is impressive, but their "knowledge" is limited to what they were trained on. But that's not the limit of their abilities. By incorporating other data such as external APIs, they can be made much more reliable and effective.

Apostles Church in Raleigh has welcomed about 25 people who came to the U.S. after the Taliban took over.

Many things about the Trump administration's new global tariffs make little sense. Those tariffs are a huge tax increase on American consumers and

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U.S. national-security leaders included me in a group chat about upcoming military strikes in Yemen. I didn’t think it could be real. Then the bombs started falling.