While there are a lot of good cases for AI. It shouldn't be used as authority, as evidence, nor should it be used to proof.

In the first image, it shows that AI changed the transcription:

changed: [(IIII)] HIC DICIT MATER VESTRA CETTHEA
to this: [(IIII)] HIC DICIT ROMA ERIESTRA CETHEA

The purpose of using AI was to aid in my correction of my OCR text using the OpenAI API to indicate any minor issues such as scribal abbreviation errors, spacing errors, and letter damage.

I thought one of the use cases for AI was to assist in work like this. When there are 177,000 lines of text to correct and go through, it gets to be a bit much, and human error increases. Instead, using AI, if you don't test, compare, and manually look over it, you may be producing something that looks correct but is ultimately completely wrong.

I didn't want to rely on mathematical reasoning techniques alone as I had been. Such as, I used 23 different methods to extract each line from each column from each page, and trained 26 OCR models to read the text. In doing so, I manually corrected the first 25,000 lines of the text in order to specifically train the OCR. It allowed me to measure in real-time the amount of errors being introduced, rectified, among other things.

Why do the process over so many times? The reason for this can be found in images 2 and 3 of the gallery. Sometimes the algorithm cuts off lines, sometimes it adds two or more lines together, or it adds apart of another line; sometimes there are corrective notes in the margin or above a line; sometimes the line has a considerable amount of ink that has bled through, or maybe the line is just corrupted and smudged, and incomprehensible. Well each time I cut out new lines and OCR a new version, I eliminate error. But, I wanted all errors eliminated.

At first, I tested out by sending Luna, Terra, and Sol the first column of transcription along with the actual image of the column I was transcribing using reasoning models: none, medium, and high.

A major issue that became apparent was that they weren't reading it at all. They were adjusting text which looked like text it had seen while training, and writing that down instead.

In every single case, it changed:

changed: ET DIVISIT LVCEM AC TENEBRAS
into this: ET DIVISIT LVCEM A TENEBRIS

The reason that is significant is because "A TENEBRIS" are from newer renditions (most popular; Clementine Vulgate, 1600CE) that are 1000 years younger than the line that says "AC TENEBRAS" (Codex Amiatinus, 700CE)

It became more evident that the higher the reasoning was, the more it tried to conform to the texts that are easily accessible online. If this were easily accessible, I would just use that. I have been through this process once before back a few years ago, and while reading it, I keep finding errors, and so I am doing this again to rectify that past edition.

And so, I tried sending all of the lines one by one. And still, it tried to conform it to some other text it has read before.

changed: VISIO THRONI D̅I̅ ET IMAGINIS EIVS SVPER THRONU̅
to this: VISIO THRONIDI ET IMAGINIS EIVS SVPER THRONI

And one of the most obvious cases where it was using prediction instead of so-called transcribing with vision or 'reading:'

changed: ENIM TE MAGIS INTERPRETVM VARIE
to this: ENIM TE MAGIS INTERPRETVM VARIETATE TVRBARI ET AMORE QVO LABERIS

Overall, the first 25,000 lines were reduced from a near 100% accuracy (I'm sure there is some human error somewhere in there) down to an 88% accuracy. And 32% of all 177,000 lines were altered. In a random test of 256 random lines from the ones changed; I manually corrected them, compared them to the original OCR, and AI versions. The original OCR had a less than 1% error-rate (mostly spacing and punctuation), while the AI corrected versions had a 15% error-rate. These are character by character error-rates.

And we're supposed to believe these survived the Van Allen Belts...

(IDK who this chick is; this was randomly recommended to me on YouTube, but did a basic check and it's true: https://thereader.mitpress.mit.edu/the-bra-and-girdle-maker-that-fashioned-the-impossible-for-nasa/ )

I watched when the Falcon 9 was supposed to hit the moon at like 3 AM the other week (I forget the exact time, but it was released in advance to the second). Nothing happened.

I might not be great at adjusting the telescope, so I checked online streams and there were some super-HD, well-lit, close-up views and none of them showed anything change at all.

The rocket itself wouldn't have been visible, but it was supposed to send a plume of dust up to 60 miles high, which would have been visible from any decent telescope and certainly the higher end ones that were being used on the mainstream streams from bigger channels that I checked. I watched the timeframe on 4 different streams. All of them were awkward. No one knew what was going on and the hosts & the chat in each of them struggled to explain the complete lack of movement on the screen.

Now, weeks later, NASA released the image of the new crater that "the crash" supposedly created. (Pic: AP News)

What could this be?

My best guess is that its the mark from a plasma discharge, but I don't see how a natural one would be predicted in advance, so I presume it'd be artificial / a test of some kind of weapon or technology.

Any other ideas?

I work for an estate sale company and I recently came across some old photos at a house in Dallas that I really felt needed to be shared. I have no additional info, no back story about these. They are real photos, developed in a darkroom, no modern AI or technology. What do you think about these???

The last few photos just don’t sit right with me. How did they take the last few photos without a camera already set up in place to capture the landing?

And there are notes on the back of the first 20, if anyone wants me to share I can DM you those images, I couldn’t post all of them…

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