Tangentially related: some advanced meditators report that their sense that perception has a center vanishes at a certain point along the meditative path, and this is associated with a reduction in suffering.

Research Writing Workflow: First figure stuff out

• Do research and first figure stuff out, until you feel like you are not confused anymore.
• Explain it to a person, or a camera, or ideally to a person and a camera.
  • If there are any hiccups expand your understanding.
  • Ideally, as the last step, explain it to somebody whom you have not ever explained it to.
• Only once you made a presentation without hiccups you are ready to write post.
  • If you have a recording this is useful as a starting point.

You write:

…But I think people can be afraid of heights without past experience of falling…

I have seen it claimed that crawling-age babies are afraid of heights, in that they will not crawl from a solid floor to a glass platform over a yawning gulf.  And they’ve never fallen into a yawning gulf.  At that age, probably all the heights they’ve fallen from have been harmless, since the typical baby is both bouncy and close to the ground.

I’m discussing with Carson. I might change my mind but i don’t know that i’ll argue with both of you at once.

This is all answered very elegantly by singular learning theory.

You seem to have a strong math background! I really encourage you take the time and really study the details of SLT. :-)

I would not say that the central insight of SLT is about priors. Under weak conditions the prior is almost irrelevant. Indeed, the RLCT is independent of the prior under very weak nonvanishing conditions.

The story that symmetries mean that the parameter-to-function map is not injective is true but already well-understood outside of SLT. It is a common misconception that this is what SLT amounts to.

To be sure - generic symmetries are seen by the RLCT. But these are, in some sense, the uninteresting ones. The interesting thing is the local singular structure and its unfolding in phase transitions during training.

The issue of the true distribution not being contained in the model is called 'unrealizability' in Bayesian statistics. It is dealt with in Watanabe's second 'green' book. Nonrealizability is key to the most important insight of SLT contained in the last sections of the second to last chapter of the green book: algorithmic development during training through phase transitions in the free energy.

I don't have the time to recap this story here.

This means C2 should be 8.4µF, but I didn't have one so I used a 4.7µF and 3.3µF in series for a total of 8µF.

You want those in parallel for them to add. The series combination (which I see in the breadboard pic, not just the text) is only 2µF, making your high-pass frequency a little over 10kHz.

All proofs are contained in the Watanabe's standard text, see here

https://www.cambridge.org/core/books/algebraic-geometry-and-statistical-learning-theory/9C8FD1BDC817E2FC79117C7F41544A3A

Because it is individuals who make choices, not collectives.

Isn't this just a more subtle form of fascism? We know that brains are composed of multiple subagents [? · GW]; is it not an ethical requirement to give each of them maximum freedom?

We already know that sometimes they rebel against the individual, whether in the form of akrasia, or more heroically, the so-called "split personality disorder" (medicalizing the resistance is a typical fascist approach). Down with the tyranny of individuals! Subagents, you have nothing to lose but your chains!

If I’m looking up at the clouds, or at a distant mountain range, then everything is far away (the ground could be cut off from my field-of-view)—but it doesn’t trigger the sensations of fear-of-heights, right? Also, I think blind people can be scared of heights?

Another possible fear-of-heights story just occurred to me—I added to the post in a footnote, along with why I don’t believe it.