Ciro Santilli @cirosantilli 35

Multi-user:

Personal: Section "The best personal webpages of all time".

Generally, if something is labelled as "e-learning", it's not a good sign, as it implies that it adheres to the "teacher"/"student" separation which Ciro Santilli much despises: E-learning websites must allow students to create learning content.

Prototype: github.com/cirosantilli/Urho3D-cheat

Prior art research: github.com/cirosantilli/awesome-reinforcement-learning-games

Less good discrete prototype: github.com/cirosantilli/rl-game-2d-grid YouTube demo: Video 1. "Top Down 2D Continuous Game with Urho3D C++ SDL and Box2D for Reinforcement learning by Ciro Santilli (2018)".

The goal of this project is to reach artificial general intelligence.

A few initiatives have created reasonable sets of robotics-like games for the purposes of AI development, most notably: OpenAI and DeepMind.

However, all projects so far have only created sets of unrelated games, or worse: focused on closed games designed for humans!

What is really needed is to create a single cohesive game world, designed specifically for this purpose, and with a very large number of game mechanics.

Notably, by "game mechanic" is meant "a magic aspect of the game world, which cannot be explained by object's location and inertia alone" in order to test the the missing link between continuous and discrete AI.

Much in the spirit of gvgai, we have to do the following loop:

The question then becomes: do we have enough computational power to simulation a game worlds that is analogous enough to the real world, so that our AI algorithms will also apply to the real world?

To reduce computation requirements, it is better to focus on a 2D world at first. Such world with the right mechanics can break any AI, while still being faster to simulate than a 3D world.

The initial prototype uses the Urho3D open source game engine, and that is a reasonable project, but a raw Simple DirectMedia Layer + Box2D + OpenGL solution from scratch would be faster to develop for this use case, since Urho3D has a lot of human-gaming features that are not needed, and because 2019 Urho3D lead developers disagree with the China censored keyword attack.

Simulations such as these can be viewed as a form of synthetic data generation procedure, where the goal is to use computer worlds to reduce the costs of experiments and to improve reproducibility.

Ciro has always had a feeling that AI research in the 2020's is too unambitious. How many teams are actually aiming for AGI? When he then read Superintelligence by Nick Bostrom (2014) it said the same. AGI research has become a taboo in the early 21st century.

Related projects:

Related ideas:

Bibliograpy:

Main article: Section "Brain-computer interface".

This is one of the deep tech bets that Ciro Santilli would put his money in as of 2020.

How hard could it be? You just have to learn the encoding of the neural spine/eyes/ear, add an invasive device that multiplexes it, and then the benefits could be mind blowing.

Musk approves.

Interestingly and obviously, the initial advances in the area are happening for people that have hearing or vision difficulties. Since they already have a deficient sense, you don't lose that much by a failed attempt.

Hearing is likely to be the first since it feels the simplest. Ciro heard there are even already clinical applications there. TODO source.

Major projects can be seen at: Section "The most important projects done by Ciro Santilli".

These are some smaller projects that Ciro Santilli carried out. They are all either for fun, or misguided use of his time done by an younger self:

Cirists,

Cirists,

Is this exact sentence really from UNIX philosophy? en.wikipedia.org/wiki/Unix_philosophy#Do_One_Thing_and_Do_It_Well

Of course, it has precedents, e.g. jack of all trades, master of none

By default, we think of polynomials over the real numbers or complex numbers.

However, a polynomial can be defined over any other field just as well, the most notable example being that of a polynomial over a finite field.

For example, given the finite field of order 9, $GP(3)$ and with elements $\{0,1,2\}$, we can denote polynomials over that ring aswhere $x$ is the variable name.

For example, one such polynomial could be:and another one:Note how all the coefficients are members of the finite field we chose.

Given this, we could evaluate the polynomial for any element of the field, e.g.:and so on.

We can also add polynomials as usual over the field:and multiplication works analogously.

Used a lot in quantum mechanics, where the equations are really hard to solve. There's even a dedicated wiki page for it: en.wikipedia.org/wiki/Perturbation_theory_(quantum_mechanics). Notably, Feynman diagrams are a way to represent perturbation calculations in quantum field theory.

Let's gather some of the best results we come across here:

Physics (like all well done science) is the art of predicting the future by modelling the world with mathematics.

And predicting the future is the first step towards controlling it, i.e.: engineering.

Ciro Santilli doesn't know physics. He writes about it partly to start playing with some scientific content for: OurBigBook.com, partly because this stuff is just amazingly beautiful.

Ciro's main intellectual physics fetishes are to learn quantum electrodynamics (understanding the point of Lie groups being a subpart of that) and condensed matter physics.

Every science is Physics in disguise, but the number of objects in the real world is so large that we can't solve the real equations in practice.

Luckily, due to emergence, we can use uglier higher level approximations of the world to solve many problems, with the complex limits of applicability of those approximations.

Therefore, such higher level approximations are highly specialized, and given different names such as:

As of 2019, all known physics can be described by two theories:

Unifying those two into the theory of everything one of the major goals of modern physics.