In a big pond, it is irrelevant how many people hate you, dislike you or even tepidly like you. All that matters is how many people love you.

If you publish a work on the Internet, the amount of negative feedback equals the number of people $0\le N<8\times {10}^9$ who view the work times the density $0<\rho <1$ of critics among them. If $N>0$ and $\rho \in (0,1)$ then $N\rho >0$. In other words, the only way to escape Internet criticism is if nobody reads anything you publish.

On the other hand, if you create good work then lots of people will read it and $N\rho$ will increase. People criticizing your work means people are paying attention to you. Lots of people criticizing your work is a sign lots of people are viewing it. Lots of people criticizing you is inevitable once enough people know who you are.

Ignoring the Negative

57. There are two red flags to avoid almost all dangerous people: 1. The perpetually aggrieved ; 2. The angry.

―100 Tips for a Better Life by Ideopunk

Most criticism comes from the angry and aggrieved. It is trivial to dismiss these people in meatspace. It is harder to do so on an pseudonymous text-based online forum.

I think we can create similar filters for the online world.

• Ignore anyone who does not refute the central thesis.
• Ignore arguments that do not endorse an alternative thesis.
• Ignore comments that persuade instead of explaining.

[Book Review] Surfing Uncertainty

Surfing Uncertainty is about predictive coding, the theory in neuroscience that each part of your brain attempts to predict its own inputs. Predictive coding has lots of potential consequences. It could resolve the problem of top-down vs bottom-up processing. It cleanly unifies lots of ideas in psychology. It even has implications for the continuum with autism on one end and schizophrenia on the other.

The most promising thing about predictive coding is how it could provide a mathematical formulation for how the human brain works. Mathematical formulations are great because once they let you do things like falsify experiments and simulate things on computers. But while Surfing Uncertainty goes into many of the potential implications of predictive codings, the author never hammers out exactly what "prediction error" means in quantifiable material terms on the neuronal level.

This book is a reiteration of the scientific consensus^[1]. Judging by the total absense of mathematical equations on the Wikipedia page for predictive coding, I suspect the book never defines "prediction error" in mathematically precise terms because no such definition exists. There is no scientific consensus.

Perhaps I was disappointed with this book because my expectations were too high. If we could write equations for how the human brain performs predictive processing then we would be significantly closer to building an AGI than where we are right now.

Now me, you know, I really am an iconoclast. Everyone thinks they are, but with me it’s true, you see…

―Lonely Dissent by Eliezer Yudkowsky

…because I used to work as a street magician.

An aircraft carrier costs $13 billion. An anti-ship cruise missile costs $2 million. Few surface warships survived the first day of the Singularity War.

A cruise missile is a complex machine, guided by sensitive electronics. Semiconductor fabricators are even more complex machines. Few semiconductor factories survived the nuclear retaliation.

A B-52 Stratofortress is a simpler machine.

Robert (Bob) Manchester's bomber flew west from Boeing Field. The crew disassembled their landing gear and dropped it in the Pacific Ocean. The staticy voice of Mark Campbell, Leader of the Human Resistance, radioed into Robert's headset. Robert could barely hear it over the noise of the engines. He turned the volume up. It would damage his hearing but that didn't matter anymore. The attack wouldn't save America. Nothing could at this point. But the attack might buy time to launch a few extra von Neumann probes.

The squadron flew over miles after miles of automated factories. What was once called Tianjin was now just Sector 153. The first few flak cannons felt perfunctory. The anti-air fire increased as they drew closer to enemy network hub. Robert dropped the bombs. The pilot, Peter Garcia, looked for a target to kamikaze.

They drew closer to the ground. Robert Manchester looked out the window. He wondered why the Eurasian AI had chosen to structure its industry around such humanoid robots.

These are my thoughts on Distribution of N-Acetylgalactosamine-Positive Perineuronal Nets in the Macaque Brain: Anatomy and Implications by Adrienne L. Mueller, Adam Davis, Samantha Sovich, Steven S. Carlson, and Farrel R. Robinson.

A critical period in neuronal development is a time of synaptic plasticity. Perineuronal Nets (PNNs) "form around neurons near the end of critical periods during development". PNNs inhibit the formation of new connections. PNNs inhibit plasticisty. We believe this to be causal because^[1] "[d]issolving them in the amygdala allowed experience to erase fear conditioning in adult rats, conditioning previously thought to be permanent."

PNNs surround more neurons in some parts of the brain than others. In particular, "PNNs generally surrounded a larger proportion of neurons in motor areas than in sensory areas". For example, "NNs surround almost 50% of neurons in the ventral horn of the cervical spinal cord but almost none of the neurons in the dorsal horn." We know from other research^[2] that motor control is associated with the ventral spinal cord whereas sensory input is dorsal.

PNNs are shown in green [below].

Here is a graph of PNNs in each brain region [below].

The cerebral cortex stands out as having few PNNs everywhere sampled. This makes sense if the cerebral cortex needs to be adaptable and therefore plastic. The most PNNs were discovered in the cerebellar nucleus, a motor structure.

The distribution of PNNs is evidence that motor areas are less plastic than sensory areas. If true, then sensory input may involve more computation than motor output.