3 ms·
> you still need somebody to drive the AI and validate or correct their outputs 100% visual inspection catches only about 80% of the defects. The following is
by ok_dad 2y ago
> you still need somebody to drive the AI and validate or correct their outputs
100% visual inspection catches only about 80% of the defects.
The following is a classic example from QC circles (I used to run incoming QC at a medical device factory). Count the number of F’s in the paragraph below:
> THE NECESSITY OF TRAINING HANDS FOR FIRST-CLASS FARMS IN THE FATHERLY HANDLING OF FRIENDLY FARM LIVESTOCK IS FOREMOST IN THE MINDS OF FARM OWNERS. SINCE THE FOREFATHERS OF THE FARM OWNERS TRAINED THE FARM HANDS FOR THE FIRST-CLASS FARMS IN THE FATHERLY HANDLING OF FARM LIVESTOCK, THE OWNERS OF THE FARMS FEEL THEY SHOULD CARRY ON WITH THE FAMILY TRADITION OF TRAINING FARM HANDS IN THE FATHERLY HANDLING OF FARM STOCK BECAUSE THEY BELIEVE IT IS THE BASIS OF GOOD FUTURE FARMING.
How many did you get?
The correct answer is four dozen (I wanted to make the number harder to calculate before you count them).
Having software devs become some sort of QC inspectors for AI code sounds like a fucking nightmare to me, and I know how much of a nightmare QC in a factory is and how many defects escape both the design and the manufacturing process even with very strict QC.
- murderfs 2y ago> The correct answer is four dozen (I wanted to make the number harder to calculate before you count them). No it isn't? I counted 34, and a python oneliner agrees.
- ok_dad 2y agoGood job, I guess, I was doing that for the comment-bait to get people to count it, not with Python though (is a Python one-liner visual?). In any case, go read stuff from Deming and Juran and others in manufacturing quality, and you will still see that 100% inspection is not enough.