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Understanding AI Models

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5 parts · about 51 min

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Start with part 1 What Is a Decision Model? Jev, Clef and the AI That Only Chooses
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Understanding AI Models

5 parts

Core path — read in order

  1. 01 What Is a Decision Model? Jev, Clef and the AI That Only Chooses A decision model returns a probability for every pre-listed option in one forward pass and writes no text. Here is how it differs from LLM JSON output, where Jev and Clef stand, and when not to use one. 7 min
  2. 02 One Forward Pass, Then Probabilities: How Decision Models Work and Are Trained A decision model reads the logits of listed options after one forward pass and turns them into probabilities. Jev discloses RLCD but not its loss; open replicas publish their heads. 8 min
  3. 03 Can You Trust the Probability? Testing a Decision Model on 77 PubMed Papers A decision model's probability is not how sure it is. On 77 PubMed papers, see how to check calibration and set a threshold from coverage and accuracy. 15 min
  4. 04 Running a Decision Model on a Mac: Question Design and Local Deployment Ask one thing per question, with mutually exclusive options and an other. This covers the nine study types and Clef-flash speed on a Mac and on NVIDIA. 14 min
  5. 05 Ask before the agent acts: gate tool calls with a decision model Rules set the floor for a tool call, and a decision model may only tighten it. Use 20 synthetic calls to choose a hosted API, open weights, or raw logits. 7 min