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longformThe machine: how we run a studio on AI, in public
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threadEmail Hero GIF
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threadIllustration
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threadPublicist
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threadVirtual Reality
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threadFrom n8n to typed Pydantic Python (workflows as structured data)
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threadMinus the Hype
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+ output-policy publish set · 7 (blog · email · social · sms) — click any to open its granular page
Blog
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The Internet of Things, demystified: when connected devices earn their keep
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Machine Learning: the part of AI that learns from your data. Here is when it pays and when a simple rule does the job cheaper.
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Machine Learning plainly: it finds patterns in your data so a system can predict, sort, or score without hand-written rules.
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Read machine learning minus the hype on when learning models earn their cost at temerarii.com/machine-learning-minus-the-hype.
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The honest part: ML needs clean, labelled data. We do that groundwork first or the model guesses.
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Not every problem needs a model. Sometimes a simple rule is cheaper, faster, and easier to defend.
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We measure an ML project by the decision it improves, not the accuracy number on a slide.
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