Ciro Santilli @cirosantilli 37

This was the first large part of the genome that was sequenced, in 1981: Cambridge Reference Sequence. Presumably they picked it because it is short and does not undergo crossover.

About 16.6 kbp:

TODO: many places say "exactly" 16,569, it seems that variable number tandem repeat are either rare or don't occur!

One of the things Ciro Santilli most deeply despises.

Real luxury is to understand quantum field theory and number theory.

Clothing/jewelry/car luxury is at worst a way to show off. And at best a replacement for nature/the countryside. People living in big cities have lost nature, and to some, looking at luxury goods (or watching television) serves as a (unsatisfactory) replacement.

Ciro Santilli took courses once upon a time, maybe that has influenced his passion? Ciro Santilli's musical education.

Something is useful if it either:

Given enough computational power per dollar, AGI is inevitable, but it is not sure certain ever happen given the end of end of Moore's Law.

Alternatively, it could also be achieved genetically modified biological brains + brain in a vat.

Imagine a brain the size of a building, perfectly engineered to solve certain engineering problems, and giving hints to human operators + taking feedback from cameras and audio attached to the operators.

This likely implies transhumanism, and mind uploading.

Ciro Santilli joined the silicon industry at one point to help increase our computational capacity and reach AGI.

Ciro believes that the easiest route to full AI, if any, could involve Ciro's 2D reinforcement learning games.

Related: Dirac equation vs quantum electrodynamics.

See: math.stackexchange.com/questions/579453/real-world-application-of-fourier-series/3729366#3729366 from heat equation solution with Fourier series.

Separation of variables of certain equations like the heat equation and wave equation are solved immediately by calculating the Fourier series of initial conditions!

Other basis besides the Fourier series show up for other equations, e.g.:

TEM: sample has to be very thin, you get a 2D image. Higher resolution possible.

SEM: sample does not need to be ultra thin, you get a 3D image. Lower resolution possible.