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Related reading: near vs far transfer when evaluating cognitive training claims #7

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@connerlambden

Interesting personalized cognitive-training framing (esp. for cognitive health research contexts).

One literature cluster that may help readers calibrate outcome claims for any cognitive-training chatbot / drill set:

  1. Gains on trained tasks (near transfer) — common
  2. Gains on similar untrained tasks — mixed
  3. Broad fluid-intelligence / general-ability gains (far transfer) — weak or absent under active controls in many WM / commercial training reviews

That split is useful even when the intervention is conversational rather than dual n-back.

I keep a short open map of that claim-size landscape:

https://intelligencemax.ai/guide

Feel free to ignore. Disclosure: I build IntelligenceMax (adaptive reasoning practice). Not claiming it prevents AD or raises general intelligence.

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