In order to fulfill that dream, AI must be sentient, and that requires it have consciousness.

This is a surprising statement. Why do you think so?

In order to fulfill that dream, AI must be sentient, and that requires it have consciousness.

THis is a surprising statement. Why do you think so?

If step 5 is indeed grounded in the spatial attention being on other people, this should be testable! For example, people who pay less spatial attention to other people should feel less intense social emotions - because the steering system circuit gets activated less often and weaker. And I think that is the case. At least ChatGPT has some confirming evidence, though it's not super clear and I haven't yet looked deeper into it.  

The vestibular system can detect whether you look up or down. It could be that the reflex triggers when you a) look down (vestibular system) and b) have a visual parallax that indicates depth (visual system).

Should be easy to test by closing one eye. Alternatively, it is the degree of accommodation of the lens. That should be testable by looking down with a lens that forces accommodation on short distances.

The negative should also be testable by asking congenitally blind people about their experience with this feeling of dizziness close to a rim.

I asked ChatGPT 

Have there been any great discoveries made by someone who wasn't particularly smart? (i.e. average or below)

and it's difficult to get examples out of it. Even with additional drilling down and accusing it of being not inclusive of people with cognitive impairments, most of its examples are either pretty smart anyway, savants or only from poor backgrounds. The only ones I could verify that fit are:

• Richard Jones accidentally created the Slinky
• Frank Epperson, as a child, Epperson invented the popsicle
• George Crum inadvertently invented potato chips

I asked ChatGPT (in a separate chat) to estimate the IQ of all the inventors is listed and it is clearly biased to estimate them high, precisely because of their inventions. It is difficult to estimate the IQ of people retroactively. There is also selection and availability bias.

Testosterone influences brain function but not so much general IQ. It may influence to which areas your attention and thus most of your learning goes. For example, Lower testosterone increases attention to happy faces while higher to angry faces. 

I think it is often worth for multiple presentations of the same subject to exist. One may be more accessible for some of the audience.

Interesting to see this just weeks after Generalized Stat Mech: The Boltzmann Approach

there's a mental move of going up and down the ladder of abstraction, where you zoom in on some particularly difficult and/or confusing part of the problem, solve it, and then use what you learned from that to zoom back out and fill in a gap in the larger problem you were trying to solve. For an LLM, that seems like it's harder, and indeed it's one of the reasons I inside-view suspect LLMs as-currently-trained might not actually scale to AGI. [bold by me]

But that might already no longer be true with model that have short term memory and may might make moves like you. See my Leave No Context Behind - A Comment.

If I haven't overlooked the explanation (I have read only part of it and skimmed the rest), my guess for the non-membership definition of the empty string would be all the SQL and programming queries where "" stands for matching all elements (or sometimes matching none). The small round things are a riddle for me too.