This is what the ARC-AGI test by Chollet has also revealed of current AI / LLMs. They have a tendency to approach problems with this trial and error method and can be extremely inefficient (in their current form) with anything involving abstract / deductive reasoning.

Most LLMs do terribly at the test with the most recent breakthrough being with reasoning models. But even the reasoning models struggle.

ARC-AGI is simple, but it demands a keen sense of perception and, in some sense, judgment. It consists of a series of incomplete grids that the test-taker must color in based on the rules they deduce from a few examples; one might, for instance, see a sequence of images and observe that a blue tile is always surrounded by orange tiles, then complete the next picture accordingly. It’s not so different from paint by numbers.

The test has long seemed intractable to major AI companies. GPT-4, which OpenAI boasted in 2023 had “advanced reasoning capabilities,” didn’t do much better than the zero percent earned by its predecessor. A year later, GPT-4o, which the start-up marketed as displaying “text, reasoning, and coding intelligence,” achieved only 5 percent. Gemini 1.5 and Claude 3.7, flagship models from Google and Anthropic, achieved 5 and 14 percent, respectively.

https://archive.is/7PL2a

That’s certainly an oversimplification.

Science has representatives that are susceptible to the flaws in human thinking that are also apparent in religion. The recent pandemic made that very clear.

There is a scientific community that has good and bad players in it. Science doesn’t get to wash itself of human corruption just because it’s a process

There are multiple points in human history where science has overestimated itself.

In Abrahamic religions, God is all knowing, not people. Eastern religions are more abstract, some have all knowing deities and some do not.