Philip @p@qoto.org

I wonder if someone has come up with an algorithm or some other kind of mathematical structure which, if run (on a computer with infinite memory and unlimited amount of time), or if it just existed physically, would produce conscious being like us or other interesting and kinda similar self-organizing structures.

I want an environment for proofs and/or mathematical explanations, which treats them as a tree or a graph rather than text. More specifically, I want to be able to write proofs like:
* Suppose A
* From A it follows that B
* C can be proved by induction
* Because B implies not C, it follows that A is false

And if you click on "C can be proved by induction", you get a more detailed explanation of how that happens:
* What property exactly we're proving by induction
* How base case is proved
* How inductive step is proved

And there somewhere if you see a logical step and you're not sure what theorems we invoke to prove it, you click on it and see "by lemma 2.2 (ii)"

There's an article by Leslie Lamport (link to article: https://www.microsoft.com/en-us/research/uploads/prod/2016/12/How-to-Write-a-21st-Century-Proof.pdf; link to hacker news discussion: https://news.ycombinator.com/item?id=17430577)
in which he advocates writing a more structured way of writing proofs, which goes like this:

1. A
2. A implies B
3. not C
4. B implies C, hence not B, hence not A

Proof of 1:
blah blaah

...

Proof of 4:
safdlkjaslfdjafds

What other similar things are there?

http://workflowy.com/ - a TODO program where you simply have nested lists, and you can easily expand or collapse subtrees

https://waitbutwhy.com has these circles of different colors in text. Green circles are interesting footnotes, grey ones are boring footnotes. This doesn't allow creating trees of arbitrary depth but the usability of these things is very good in my opinion and perhaps we don't need that much depth.

It seems http://arbital.com/ has a thing like waitbutwhy, except it allows arbitrary depth.

I want to tell you how to form new habits and replace old ones.
Most animals including humans have this thing called Trigger-Action Patterns. It is a habit of if <specific trigger has happened> then <do specific action>. Examples: there's a bowl of chips in front of you -> take one; you open your browser -> click on [you usual first click site]; you have arrived at [specific ttain station] -> go to [specific exit]. The last one often happens to me even when I intend to go in another direction simply because I used to travel that way often when I was studying at university. Basically whenever you making a decision and often even when you are not making deliberate decisions, there's a part of your brain which votes for the action you usually do in similar situations.

Here's how to use it to create Trigger-Action Plans:
1. Identify goal. I want to learn more English words and I have an app on my phone for that.
2 and 3. Choose trigger and new action. Whenever I bring my wallet with bus card to the bus payment device (this is the trigger), I will think whether now is a good time to study using the app.
4. Rehearse. If you can do it physically by getting into situations with the trigger, do it. Otherwise visually imagine you getting into such situation, noticing the trigger and doing the action. Rehearse for 10 times

Google Trigger-Action Plans to learn more.

1. Images of cats being transformed from one to another by neural networks. http://dump.bitcheese.net/files/cucycus/output2.webm
2. Images of humans being transformed. http://dump.bitcheese.net/files/zefonac/output_humans.webm
Source: https://www.youtube.com/watch?v=MUVbqQ3STFA
#deeplearning

I have finally finished reading Thinking, Fast and Slow by Kahneman, Daniel (https://www.goodreads.com/book/show/11468377-thinking-fast-and-slow). The book is about cognitive biases, i.e. systematic patterns of how humans behaviour deviates from optimal, fast intuitive vs slow analytical mind, and choices. The author's got a Nobel prize in economics and is a smart and trustworthy (science-wise) person overall.

I am not sure if knowledge from the book is useful enough to me. It was quite boring to read. Also a few early chapters talk about psychological effects which later turned out to be weaker or to work in a different way than it was thought. To be precise, I am talking about priming and ego depletion.

It is also popular among #lesswrong crowd.

#rationality

How to get into modern classical #music: http://lukemuehlhauser.com/how-to-fall-in-love-with-modern-classical-music-4/

The guide contains the more approachable composers, modern classical music in film OSTs, and other stuff.

#introductions

Hello everyone, I am Philip, I am from Moscow, Russia. I am an MSc Data Science student.

Here's a list of my interests: #rationality #math #programming #AIAlignment #EffectiveAltruism #FOSS

Here is my goodreads profile where you can see what I have read and am reading https://www.goodreads.com/user/show/20103683-screw-driver

Smaller and possibly temporary interests:
#probability
#lesswrong
#tabletennis
#deeplearning
#science
#music
#anki
#cycling
#moscow
#psychology
#videogames
#python
#hardscifi