I simply asked ChatGPT’s DALL-E Extension:

Focusing only on the head for now, imagine that the image on the Shroud of Turin was created by radiant heat by holding the linen cloth close to a hot metal statue. Consider the fact that the image on the shroud seems to be a 3D heightmap. What might that statue look like?

It took about 7 seconds to generate the image. I provided no data or images whatsoever. I let it depend on the images and data and the interpretations that are out there. It’s a high-schoolish exercise, and it certainly doesn’t suggest anything new or insightful. I was a bit surprised that it seemed to ignore the problem of non-collimated radiation. It is just a demo of the raw power that is out there in cyber AI land. With the right details, it might generate something useful.

Could we leverage ChatGPT and other AI tools, given appropriate resources and expertise, to explore John Jackson’s Fall-Through hypothesis in new ways? Could we extend Colin Berry’s experiments? Is it possible to continue the work initiated by Ray Rogers and Bob Rucker through modeling with new AI tools?

Can ChatGPT also generate new hypotheses for our consideration?

The image below is from  Judgement Day For The Turin Shroud, p. 91, Figure 22. It has been described by Walter McCrone as “The tape of a Shroud ‘blood-image’ area 3-CB showing only a red ochre paint image also at high magnification.” It is obviously controversial.

AI tools designed for medical and forensic laboratories are starting to come online. Still costly and still being tested, they are intended to give human microscope analysts a run for the money. 

Incorporating artificial Intelligence into the examination of the Shroud’s microscopic evidence can fundamentally amplify the analytical capabilities of Shroud science, akin to mobilizing a million expert eyes to perform millions of hours of analysis in a fraction of the time. This metaphorical ensemble of “AI experts” operates with a level of detail and precision that mirrors, and often surpasses, human capabilities, conducting intricate analyses almost instantly. AI systems can meticulously scrutinize all of the photomicrographs and digitized samples, identifying patterns, anomalies, and correlations that might elude even the most seasoned researchers. AI can provide detailed explanations for its findings, drawing on vast repositories of data and prior knowledge, thereby enhancing our understanding of the Shroud. 

This approach can democratize Shroud science by making comprehensive and expert-level analysis accessible to researchers everywhere, regardless of their physical access to high-caliber microscopes or the human expert manpower typically required for such detailed work, in essence, paving the way for breakthroughs in our understanding of the Shroud. It might certainly minimize the controversy.