I don't really see how you got to your comment from what I quoted. However, somewhat relatedly, I proposed a thought experiment about this in the comments for Opus 4.7[0]:
> It's April, 1991. Magically, some interface to Claude materialises in London. Do you think most people would think it was a sentient life form? How much do you think the interface matters - what if it looks like an android, or like a horse, or like a large bug, or a keyboard on wheels?
> I don't come down particularly hard on either side of the model sapience discussion, but I don't think dismissing either direction out of hand is the right call.
With the amount of data these models have, they should be much more capable if there was an actual intelligence behind it. If you saw someone running into a wall continuously until you showed them how to use a door, even though they have seen people use doors a million times, what would you call that?
The fact that Anthropic needs to poke, prod, and guide these models to behave in the desired way does not give the impression of intelligence. It gives the impression of a complicated automaton.
This is such a bizarre statement, you speak as if you have any understanding of how much data "should be" required to make an intelligence but frankly you don't know. None of us know.
I am not talking about how much data is required to make intelligence. I am talking about how it uses the data it already has. It can tell you about every scam in the book, research about the scams, how to spot scams, who does the scamming, etc. Everything under the sun about scams. However, without the “skill” included in a prompt it will fall for scams.
If I may slightly tweak your example to highlight why I find it very flawed:
> It's April, 1891. Magically, a drone swarm with lights piloted to show a face [0] materialises above London. Hidden speakers command the public to listen, for this is their Gods arrival. Do you think most people would think this was a religious entity? What if the drone pilots decided to adjust to something the local populous would expect to see during the second coming, does that matter?
We cannot, nor should we discard what we know about LLMs and their limitations. Such examples are not really helpful and it is very reductive to take the "walks like a duck" approach to autoregressive models in 2026, when we have ample evidence that these, while powerful and capable in a lot of use cases, are not in any way comparable to actual reasoning. With EBM [1] we already have empirical evidence that other solutions can get us closer to actual artificial reasoning (though whether these get us fully there remains to be seen, I tend to lean on "extraordinary evidence" for any such statement at this stage).
