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Build Your Own Local AI Stack: A Session on Models, Hardware, and Quantization

How to choose an open-weight AI model that fits your local machine, runs without a cloud subscription, and can't be shut down by a vendor.

This morning, I went live to discuss three things you should know before you set up a local AI model on your own machine:

  1. Where the model came from.

  2. What your hardware allows.

  3. And a concept called quantization that decides whether the model runs smoothly on your machine or slows everything down.

Watch the recording above.

Every step-by-step build I’ve published over the last two months lives in one place, from your first local AI agent on a laptop to wiring one into your team’s data. The n8n local tutorial alone gets you a private AI on your machine in about thirty minutes, no cloud, no API keys.

Get them here: https://www.thedataletter.com/p/build-ai-tools-you-control

Tomorrow’s article on The Data Letter is a build that takes the three questions from this morning’s live, applies them to your machine, and walks you through setting up a local model you can connect to the work you already do every day.

After the Fable 5 fiasco, it’s time to take ownership of your own stack seriously.

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