Samsung + Mistral: When AI Flags a Defect, How Often Is It Right?
Samsung + Mistral: when AI flags a chip defect, how often is it right? Samsung’s 9 September 2026 announcement describes plans to use on-premises AI in semiconductor operations, including defect detection and equipment optimization. It states goals, not a measured yield improvement. Here is our independent, fictional inspection run — NOT Samsung or Mistral performance data. Of 1,000 parts, 20 are defective and 980 are good. A detector catches 90% of defects (18) but also flags 5% of good parts (49). It produces 67 alerts, of which only 18, or 26.9%, correspond to real defects. Two defects are missed; 931 good parts are cleared. The denominator matters: detection rate is 18/20; alert precision is 18/67. Neither alone establishes manufacturing value. A flagged part is not automatically scrapped: review, retesting and process decisions change the economic result. Save three questions for the next factory-AI headline: What is the real defect base rate? How much review and downtime do ...