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Apache 2.0, MIT, Llama community licenses, and research-only terms give you very different rights. A plain-English guide to what you can legally do with a downloaded model.
Read article →Cloud inference prices fell roughly 80 percent between 2025 and 2026. Here is what that does to the local-versus-cloud calculation, and why cost is now the wrong reason to choose either one.
Read article →Open weights, open source, and open license are three different claims. What each one gives you, what it withholds, and which one matters if you want AI that runs on your own machine.
Read article →Both labs ship excellent models. For rewriting work messages the differences that matter are not the ones the benchmarks measure. A practical comparison, including where neither is the answer.
Read article →Alibaba ships Qwen models faster than anyone can track. A guide to which sizes matter, what the naming means, and why the small ones are the important ones.
Read article →Hunyuan 3.0 shipped open weights in July 2026 with three selectable inference modes. Why letting the user choose how hard the model thinks is the most practical feature of 2026.
Read article →Every hosted model you build a habit on will eventually be retired. How to notice early, migrate without breaking your prompts, and keep one option that cannot be taken away.
Read article →Open weights turn a data-handling promise into an architectural fact. Why that distinction is the whole argument for anyone writing client, patient, or contract text.
Read article →Client contracts increasingly restrict AI use. Here is how to read the common clause types, what they cover, and how to stay compliant without giving up tooling.
Read article →AI detection tools are being pointed at work emails, reports, and applications. Here is what their scores mean, where they fail, and what to do if you are accused.
Read article →Not typos. The small English choices that make readers act on something different from what you intended, and how to catch them before sending.
Read article →The same message reads as efficient in Amsterdam and rude in Tokyo. Practical adjustments for directness, hierarchy, and timing across a distributed team.
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