I was going to include this in my ongoing thread on AI learnt "something" from the Physical & Life Sciences Forum highlighting the progressive improvement in AI over the past year but decided on a new thread as it pertains to an issue raised in the Where are the current ripples from Noah's Flood? thread.
The issue relates to Petrie’s No. 7 granite core sample which is somehow considered as evidence the ancient Egyptians had access to granite cutting technology way beyond the capabilities of modern equipment.
Before proceeding astronomers do not directly measure angular separation or angular diameters of objects such as double stars or planets as they did in the old days using devices such a visual micrometer, instead they image the object and use software to accurately measure the pixel separation.
By knowing the image scale, they are able to convert pixel separation into angular distances which are far more accurate than the old methods.
One of the problems in the thread there was not enough information on the pitch or separation of the groove lines in Petrie’s sample.
I assigned the task to GPT-4o to extract information from the image on the pitch in the image corresponding to each turn or 360⁰ rotation of the tool.
It proceeded as follows.
(1) Enhance the image contrast to make the groove lines more visible.
(2) Analyse the image for the number and size of pixels.
(3) Measure the pixel separations of the grooves.
(4) The next step GPT-4o required information from me, I used Dunn’s average pitch value of 0.1”.
(5) Average the pixel separations and use the conversion S = (Average pitch in inches/Average pixel separation) = 0.1/15 = 0.00667”/pixel which is the image scale.
(6) Convert pixel separation to pitch using the image scale.
(7) Calculate the average pitch value and the standard deviation (%).
(8) Plot pitch against turn number and perform a quadratic polynomial regression of degree 2 to find the curve of best fit.
The next post is comparing the Petrie data extracted by GPT-4o to tolerances for pitch when drilling granite using current technology of diamond tipped drills with RPMs in the range of 1000-6000 RPM depending on the core size of the granite.
The issue relates to Petrie’s No. 7 granite core sample which is somehow considered as evidence the ancient Egyptians had access to granite cutting technology way beyond the capabilities of modern equipment.
Before proceeding astronomers do not directly measure angular separation or angular diameters of objects such as double stars or planets as they did in the old days using devices such a visual micrometer, instead they image the object and use software to accurately measure the pixel separation.
By knowing the image scale, they are able to convert pixel separation into angular distances which are far more accurate than the old methods.
One of the problems in the thread there was not enough information on the pitch or separation of the groove lines in Petrie’s sample.
I assigned the task to GPT-4o to extract information from the image on the pitch in the image corresponding to each turn or 360⁰ rotation of the tool.
It proceeded as follows.
(1) Enhance the image contrast to make the groove lines more visible.
(2) Analyse the image for the number and size of pixels.
(3) Measure the pixel separations of the grooves.
(4) The next step GPT-4o required information from me, I used Dunn’s average pitch value of 0.1”.
(5) Average the pixel separations and use the conversion S = (Average pitch in inches/Average pixel separation) = 0.1/15 = 0.00667”/pixel which is the image scale.
(6) Convert pixel separation to pitch using the image scale.
(7) Calculate the average pitch value and the standard deviation (%).
(8) Plot pitch against turn number and perform a quadratic polynomial regression of degree 2 to find the curve of best fit.
The next post is comparing the Petrie data extracted by GPT-4o to tolerances for pitch when drilling granite using current technology of diamond tipped drills with RPMs in the range of 1000-6000 RPM depending on the core size of the granite.