Table of Contents

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1. discussion   draft another

Discussion is telling any idea.

  • moreover, in academic context, discussion also refer to the activity of telling any idea in written form and pass it to peers, so that the idea goes through the peers(for review and sharing).
  • sometime it also refer to the activity of multiple people telling their ideas on the same topic.
  • foundation knowledge

2. linear optimization problem

optimization problem where in the constraints, all occurances of input is linear(to the power of 1).

  • example: \[$ f(n) = n \\ constraints: \\ n < 5 \]

3. The slow arrow of beauty

The noblest kind of beauty is that which does not transport us suddenly, which does not make stormy and intoxicating impressions, but that which slowly filters into our minds, which we take away with us almost unnotioced, and which we encounter again in our dreams; but which, however, after long lain modestly on our hearts, take entire posession of us, fill our eyes with tears and hearts with longing. What do we long for at the sight of beauty? we long to be beautiful. We fancy it must bring much happiness with it. But that is a mistake. – Friedrich Nietzsche, “Huamn, All too Human”, 149.

4. 85% law

85% law is an heuristic of “difficulty sweet spot”.

85% law states that highest learning rate occurs when:

  • success rate is about 85%
  • \(\frac{\text{success rate}_{\text{before practice}}}{\text{success rate}_{\text{after practice}}}\)

4.1. fact support

It is put forward by writer Scott Young in this blog.

  • this paper states 85% rule for optimal learning in the context of machine learning.
  • in his blog, Scott Young associated this with some other theories with similar statement in the context of Learning Science

5. using 85% law

By adjusting these difficulty parameters, you can affect your success rate. Make the task harder when you succeed too much, and keep the success rate around about 85%, that is about 5 success in 6 tries.

difficulty parameters
There’s handles you can adjust to affect difficulty in every practice. It’s in the form of adjusting the level of support you can consult.
define success

make a quantitative measure of success, and thus success rate. there are multiple ways for 1 activity.

activity difficulty parameters success definition
solve prolbem open book? 5 right answer in every 6?
  worked example? time?
  cheatsheet? effective step?
  without anything?  
drawing figure reference? 5 looking good out of 6?
  cheatsheet? time?
  tools?(spray, distortion) effective step?
  values? poses?
  without anything?  
programming without mouse? 5 test success out of 6?
  arrow key? 5 perfect function in 6?
  cheatsheet? 5 perfect use case in 6?
  examples?  
  lsp?  
  design doc?  
  without anything?  
(no term)
using 85% law on programming (where detailed scheme of difficulty parameters and succes definitions are elaborated.)

6. Process of improvement

6.1. circle

  1. start
  2. difficulty
  3. boredom
  4. quit

For some people, when they want to actually do something, circle often happen. They’d start, the passion would push them for a while, they may even do some early stage works, but the passion would disperse after 2 weeks, they’d get bored, and eventually quit. Thed’d end up with a lot of aborted projects.

circle.png

6.2. stairs

  1. complete first project
  2. try something new/harder
  3. use past skill for new effort(and thus the stair go higher as there’s more skills)

For some people they’d make small short-term projects, and after finishing that they’d move on to other ideas. They’d end up with a lot of finished projects

6.3. Difference between circle and stairs

The difference is whether you quit or finish your project. If you round it up with actual work, you learned, practiced skills, and have some kind of product enriching your life; if you quit, chances are you didn’t put in much actaul/effective work.

6.4. Factors between circle and stairs.

project length
short-term project are easier and more concrete to finish. some proejcts like “I’m gonna from today to forever be running at 6” is doomed to fail. projects like “run 3 times at 6 next week” is much easier and concrete, and less commitment.
focus
multi-projecting is not good idea if they are hard. Learning is hard. So if you want/need to learn something in the project, multi-projecting is doomed to fail. You better focus on finishing 1 at a time, even if they have same coursework period(same issue time/deadline).
right method
to do new thing, you need the new(for you) right method to it.
actualization > possibility
the mindset. If you put actualizing an idea higher than let them remain possibility, you are more likely to design/execute towards finishing the project, rather than daydreaming or planning. Thinking about actualization really give you a humongous motivation to get the project finished.

7. difficulty of recall/thinking

The main difficulty parameter is the context. Namely, the environment, how much complete the puzzle have already become.

  • musical example: It’s harder to remember the lyrics, lines and staging and simulate it in your mind, it’s easier to be there (in the show)and say the lyrics/staging.

8. duality

That property of 1 linear optimization problem being actually 2 linear optimization problem.

8.1. example

1 optimization problem
Finding the largest integer no less than 5
2 optimization problems
  • Finding the largest integer no less than 5
  • Finding the smallest integer no larger than 5

8.2. properties

boundary
the optimal solution to both is the same
(no term)
feasible solution to the first are all smaller than feasible solutions to the second.
feasible solution
fit in the constraint but is not optimal

9. usage/classes of zettelkasten notes

10. machine learning as autonomous system

Most system with autonomous control have self-adjust functions to maintain a given state.

This kind of control could be calculated by enginner and implemented as design, or have some learning function that adjust the adjust parameters itself.(like acceleration on some input).

To maintain a ball in a zone, an acceleration is applied based on coordination and speed.
This acceleration could be calculated by definition of zone, and some equations. Or it can be calculated with machine learning algorithm.

When full environment information is available, a deterministic normal algorithm would suffice.

When partial environment information is availabel, or information too complex, a learning algorithm may be better.(but not necessarily)

It is worth noting that learning on time sequence is emphasized in this kind of learniong algorithm, as input-output for the target function(cause-effect relationship) is given in time sequence of sensor inputs.

11. machine learning: guessing target function

For tasks where the target function is clear and universal, machine learning is redundant. You don’t need a machine learning algorithm to know that \(F = ma\)

For tasks where the target function is hard to tackle because:

  • target function is dependent on environment(personalized) song recommendation, personalized assistance prompt(time,location and app), session specific query(chatgpt session)
  • target function is too complex (thousands of parameters/influences) language-meaning

machine learning could help guessing the target function autonomously(design the learning algorithm once and use everywhere.)

12. If there’s nothing, there’s nothing to hate

observation 1
I used to like jetBrains’ logo and style, but now I hate it
observation 2
I used to like my-emacs-config’s theme, now I kind of hate it
observation 3
I used to like machine(as with Ray Daleo), now I kind of hate it because I ruined it for myself
observation 4
I used to like Doom emacs’s startup, after a while I kind of hate it because there’s a while I see it and not doing meaningful stuff, and now I like it because I’m back doing meaningful stuff with it.
observation 5
I have absolutely no opinion on the minimal startup emacs(which is empty scratch buffer), or vim(which is either straight to file or a line of text signifying it is vim.)
hypothesis
minimallism reduce association of idea-visual with feelings. That could be 1 upside of minimallism: distraction is reduced and you see clearer the real stuff.

13. connected graph via link literal

If you only create new org-roam node via link literal operation(make a [[roam:title]] link and click/follow it.), then the graph is guaranteed to be connected.

It could be proved by induction: base case being only 1 node, and doing this make it connected, and recursive step being adding a node and a link to a linked graph, which make them a linked whole.

Also note that if you only create new node with links(that is, every link is leading to a new node), there won’t be cycle, and thus would be hierarchy.

14. RSA

RSA is an asymmetric encryption method.

keys
you are given 2 keys in RSA, a public key and a private key
public key
public key consist of 2 numbers, \(e\) and \(n\).
private key
private key consist of 2 number, \(d,n\).
Encryption
Encryption is done with the public key \(e,n\).
  1. You translate the message into an really large integer \(m\).(e.g. concat all ASCII code of the characters)
  2. \(cipher = m^e \mod n\)
Decryption
Decrypition is done with private key \(d\).
  1. \(m = c^d \mod n\)
Key generation
\(e,n,d\) are generated by
  1. take 2 very large prime numbers \(p,q\), let \(n = p \dot q\)
  2. select some \(e, \text{where } 1
  3. \(\phi{n}\) is count(number less than n that coprime n).
  4. \(\phi{n} = n-1\) if n is prime number
  5. \(\phi(n) = \phi(p) \cdot \phi(q)\) if \(n = p \cdot q\)
  6. calculate \(d\) such that \(d \cdot e \equiv 1 \pmod {\phi(n)}\)
    • as \(e\) prime \(\phi(n)\), \(gcd(e,\phi(n)) = 1\)
    • which is equivalent to \(e \cdot x + \phi(n) \cdot y = 1\) \(x,y\) could be computed with Extended Euclidean Algorithm
    • which is equivalent to \(e \cdot x = (-y) \phi(n) + 1\)
    • which is equivalent to \(e \cdot x \equiv 1 \pmod {\phi(n)}\)
  • resourse
  • reminder
    • There’s a lot fuzzy joint needs rigid proof in this note. Establish them.

15. The whole of human mind   observation

  • one fun fact about human mind is that it is totally not rational.
  • you see a stuff, and immediately a framework, an idea, a structure appears out of blue.
  • a dangerous part is the implementation plan. Implementation usually take time and focus, so if you work on your implementation plan without recording them on an external media, it’s going to be forgotten or get distoreted.

16. name-spacing with zettelkasten

Zettelkasten is great way to settel rustleing ideas in mind and build sound structure in them. It is likely that you want to do anything with zettelkasten(at least at the start, when you are collecting ideas and building design)

for different projects, it’ll gradually become imperative that you don’t want them to be mixed together, majorly because the truth stand of each may be different:

  • for revising a module, you care about the specific system that would be used as correct answer. You don’t necessarily believe in them, or find them useful/interesting
  • for building a software, you care about your own abstraction and designs that are present in the software along with tech references of how you can implement them They are not true stuffs, and tend to be large in quantity
  • for noting down your thoughts, you don’t really know whether it is very stupid or worthy a second look. The soundness of them is in doubt.

The name-spacing require 2 operations:

  • search with a name-space
  • search without a name-space

There are some ways to do name-spacing with zettelkasten.

17. Tag and link: Gate and corridor

One way of perceiving usage of tags and links is:

  • tags are gates to a building
  • links are corridor navigating around once you are in

e.g: In Zettelkasten, you want few tags, few notes with tags and lots of links between notes. You can tag some navigational notes but not the notes they link to. In browsing, you want to read your notes about “machine learning”, you could search for the tag, and notes that are entrance to clusters of you machine learning notes would appear, and you could explore each cluster as you want reference: this comment

18. Todo list as reading list

reading an article is a procedure, and naturally a todo task if planned.

19. reading seq model

Reading seq model defines a Sequence data structure with 2 methods.

Sequence
is a seq with elements all object/links to reading materials
add method
how to add to the seq
consume method
how to consume element(read stuff) from the reading seq.

if one such entity is implemented, should reduce the amount of operation required to “add to reading list” and “read an article” to be one

20. minimal operations

Minimal operations is concept for algorithm or user experience, that there’s a minimal operations to achive a goal.

example:

  • in Euclidean Algorithm, you have to go through all the bits of the 2 numbers to find their GCD. There’s no way to find the GCD without going through them.
  • with text editing, the minimal operation of each text operation, like “copy this line from 2nd to 9th letter”, is 1 key press(define a function that do this stuff and bind it to a key). however, if you have too many procedures in this manner, you’ll most certainly run out of keys, at least the easy-reaching ones, and soon require paging/navigating, which would be implemented to another key, or some prefix system. And that would be y a w like vim.

integration:

21. balance minimal operation with mental load

mental load refers to the mental effort made to memorize or recall the command for operation. For instance, to remember a shortcut and what it do in a software.

Mental load could be measuered with number of spanning rules. In the worse case, the number of spanning rules would be the same as number of operations. The coresponding scenario is that there’s no structure and the association of keys and procedures are random, in which minimal operation could be achived

Mental load could be reduced with prefix/hierarchy system, visual aid, or verbal system, which trys to represent bulk of operations with few spanning rules.

For instance, in vim key-binding, verbal system is a major component. with y [motion command], a large set of copying commands is covered with mantal_laod(motion commands) + 1, like copy 2 lines below, copy 2 lines above, copy until next “f”, copy to end of line, copy till next word…

downsides: note that visual aid could be distracting, verbal system could be hard to implement, and hierarchy system is sparse and could be not too performant.

22. use n-hoffman code prefix tree to analyse minimal operation in command system

the largest number of minimal operations in a command system is equivallent to the size of longest n-hoffman code string that could represent the all operations in the command system. n refers to number of keys. n-hoffman code refers to hoffman code with each digit from set of all available keys in the command system

It is easy to see that n-hoffman code is the smallest string that allows deterministic parsing to all the operations.

with n-ary (digit system with n options each digit) representation:

  • n-ary representation make every string the largest number of minimal operations
  • with n-hoffman code prefix tree, could assign shorter codes frequent procedures, count all minimal operations and other that reflect real-life use.

23. data

24. self-evident

self-evident/instinctive is for a phenonmenon that, for a process, you could recall the whole process with ease immediately, on seeing any part of it.

  • like packaging a box: you see the tape, you know how you would wrap it around the box.

Note tha self-evdience is related to training. Some process are self-evident to some person, some don’t. For man who see tape for the first time, it may not be so self-evident how to use it. I don’t konw how to operate firearms, but for military man the guns and firing would be self-evident.

25. Being myself and Confidence and Distraction

I have a course. I have a path. There’s stuff that I feel right doing. That is what I refer to as “myself”. Stuff I think and feel right, stuff I do and feel right. Game a lot don’t feel right, think low of myself don’t feel right.

And if I don’t feel right about the 2, the mental or the physical, I lose confidence, I lose integrity, I lose sincerity. They raise doubt, they raise stress.

And How do I lose them? I don’t give them up myself, at least not consciously: There’s distractions, and I followed them. They may be primitive, that distracts me out of the nature of the very human I am and the nature of the distraction: I’ll always prioritize eating when I’m hungary; or traditional, that I have allowed them in my life in the past and they thus stayed.

And the traditional distractions is they main enemy from being myself and being confident.

26. destruct until outcome is self-evident

this is a criteria of How small should my GTD action be. Generally, in GTD we want full capture, full establishment of action, and no partial note. And we want the action to be easy to shift focus to, meaning no extra planning, no extra learning/research of how to do it: they should be done seperately or in determining the task.

Therefore, if the desired outcome is self-evident, meaning that you can immediately see how you make the outcome, you achived the 2 criteria the same time:

the information is complete
you know exatcly what to do from beginning to end.
easy focus shift
you can load the entire context (or most of it) immediately from the description.

27. Parameters to Focus.

observations/data
1
One time, I read paper and I could keep track of threads, stuffs I noticed, can skim through passages and tag them what they are talking about
2
One time, I read paper and even finishing sentence is hard. I can’t really keep track of things in my head
parameters
Hot water
drinking it.
Hot water spa
a thing I do. I blow hot water for a while and let it steam my face. get me to calm down.
Music
type of music
Happy? Musical?
Noise
Environment
stance
standing, sitting
exercise ahead
psychological factor
deadline?

28. having process cheatsheet for each procedure I perform

There should be a cheatsheet(better physical) available for each procedure that I’d perform, like literature review, reading paper…

  • establishing procedure should produce cheatsheet other than the main document [2023-05-13 Sat 16:30]

29. doubting and confidence

It apppears that it is more lovely to see:

  • people actually confident doubting themselves

than:

  • people acutally inconfident, insecure trying to act confidently [2023-05-21 Sun 15:20]

30. holistic confidence

confidence is a self-preserving state:

  • by mimicking being confident, you’ll approach actually confident
  • by being confident in part of something, you’ll approach confident in the whole of that thing
  • by posing a subset of confidence signals, the other would appear automatically

[2023-05-21 Sun 15:22]

31. external and un-logged mechnism

data
me using RH timer for pomodoro instead of org-pomodoro or org-clock-in stuff
interpretation
distributed mech
pomodoro is a mechnism to maintain level of focus/energy in a period of time. There’s no need to keep global control of it as long as it does it’s work and make the focus of that time period sharp.
time-distributed
Treating various time-periods in a day like asynchrnous nodes for processing
un-clockable activity
when doing knowledge work, sometime it’s hard to define what to do, as “finding out what to do” is the work, or the task would be “process this batch of information and make some structure out of it”, which may not success(as there’s no such structure). A large timesink activity like “process information on comp212” may be practical.
why RH timer
It have neat GUI, can stick on top, have pomodoro shortcut.

[2023-05-21 Sun 16:52]

32. desperate for ability

data
I want to be able to play something in jazz improv/comping. I want it so badly I collect everything and practice them.
interpreation
I may end up only be able to make common gibberish, went on autopilot and only play stuff I heard of. I saw that before with my 6-5-4-3 improv.
more
being able to talk all the time is a skill very much wanted. but don’t I want to speak only the gems and not discarding junks?

[2023-05-22 Mon 11:37]

33. working with other musician -> mutual knowledge

it’s important you have an expectation of what you will be making, so that you know where to build off and notice special ques and signals, stuff out of ordinary. can do it by asking for other’s practice tracks and do some little study [2023-05-22 Mon 11:55]

34. it is really different reviewing/learning for exam and reading for research or skill

  • for exam -> remembering a marked one right answer
  • for research/skill -> make stuff that make sense to you

    [2023-05-22 Mon 12:15]

35. TODO find a way to use org-capture with file-specific variables

desired outcome
a function that can use and update file-variable in an org-capture session
scenario
in licks.org, there’s an count-id(Lick No.3). How I could implement that with org-capture automatically fill in the headline [2023-05-22 Mon 12:24]

36. improvisation and research

improvisation on a number could be seen as research on a topic and have your own argument. You could just do it directly, or see some literatures of how other people think of it, and maybe build off that. e.g.: it is surprisingly hard to improvise on autumn leaves, and most recordings on spotify didn’t do much better than I do. But skimming through, you’ll find some valid ideas [2023-05-22 Mon 12:31]

37. how I can teach my piano student

the syllubus would consist of:

a Herman No.2 Piano skill set
composition of some fundamental playing skill
a Herman No.4 music research/discussion skill set
composition of some research skill for the student discuss numbers, their thoughts, and develop their arguments/own insight and implementation of musical ideas [2023-05-22 Mon 13:47]

38. TODO figure out how macOS work

desired outcome
write a tutorial about how macOS work and various APIs it exposes that one can use with program

https://developer.apple.com/library/archive/documentation/Darwin/Conceptual/KernelProgramming/Architecture/Architecture.html and maybe write some C to test it, and relate them to my usage I may stick with my macbook for quite a long time. So I hope at least I understand what I’m using.(it’s not like I’m ever going to get a linux machine) [2023-05-31 Wed 02:51]

39. localisation

a paradigm is that, instead of a master theory, a master paradigm, which should incorporate different techniques and be consistent of various observations, use very scope-specific cluster of ideas.

For example, one can approach music as there’s one correct theory of composing/instrumentation(master theory) and translate their techniques and thoughts into arguments compatible with that theory. The localisation version may be approach music as various techniques, observations and ideas, each with own data and interpretation, maybe integration. [2023-05-29 Mon 17:16]

40. taking course :(, doing it :)

it is important that you make creative/opinion decision on the thing, and finish your creative project(that is a project that is to span/implement/illustrate/expriment your opinion/idea). That way you remember of a simluation of how things may went [2023-05-28 Sun 01:29]

41. masking strategy failure

with a general simple rule, scripts/program is likely to meet special scenarios that work unexpectedly Strategies to mask these failures are:

  • specify the failure scenarios, and advise the user to avoid them
  • use guard to avoid the scenarios in program (require strategy to deal with them) it’s similar to that in behaviour tree, you can add if-then structure as first child of an or node, to mask latter children’s fialure(if they are too complex to be modified)
  • re-design with the failure scenario considered [2023-05-26 Fri 12:35]

42. use capture as bookmark inbox

Since bookmark are for later refrence, and is a type of capturing, it totally makes sense, and make me happy(don’t have to remember where and how I do bookmarking all the time) [2023-05-26 Fri 12:06]

43. literary programming vs. automation/scripts

literary programming and automation are alternatives sometimes. Some time you need a script to automatically find a class of object(like pdf files), because it’s too much trouble keeping them mannually in a text file. With literary programming such as org-babel-tangle, such burdon is elevated (when scale is small), as you can have very easy-to-understand code snippets and easy/intuitive way to run and navigate around them.

They are not entirely the same, but sometimes interchangable [2023-05-26 Fri 11:47]

44. exploring options

  • write down possible options.
  • someties you’d find simple, stupid, narrow, domain-specific ideas way better(to write, to use) than generalized, complex ones. [2023-05-26 Fri 11:44]

45. drum with bass

[2023-05-23 Tue 22:44]

46. Wes Anderson’s Mr.Fox gots interesing music

western? some parts. Some Guy Rich similar atmosphere. Snare and the horn how can I make something similar… [2023-05-24 Wed 23:56]

47. Western music - whistle

wistle accompanying snare, or very dry acoustic guitar [2023-05-25 Thu 00:17]

48. successful improvisation introduce substructure that deviates from the form   music

driving focus off. https://music.youtube.com/watch?v=XaAiNL-YJIs&list=RDATfdYmVib3Az [2023-05-22 Mon 14:45]

49. avoiding problem instead of solving it

data
there’s no known way of recovering a losed arm. There are people working on it, but the bulk of us mainly try to avoid losing an arm till the day we die. [2023-05-22 Mon 15:28]

50. Emily’s high notes are absolutely amazing!

These well-renaissant notes. so good [2023-05-23 Tue 14:05]

51. pen&paper vs. org-mode

Itis obvious they have their own strengths/weakenss:

  • pen&paper
    • slower to write words
    • can draw
    • anotate really easily
    • really easy mindmapping
    • good for drafting strucutres
  • org-mode(aka text-based computer note-taking)
    • faster(words)
    • can be searched
    • manipulation
    • completion
    • links
    • draw is really hard
    • anotate slower,
    • structural modificaiton/implication is really hard(only hiearachycal is intuitive)

[2023-05-25 Thu 13:52]

52. What to do with bully

scenario
what should we do if we encountered bullying
(no term)
ask - is justice the most important thing to you, is payback, or the balance that important to you that you should focus on that entirely
  • if not - always do the most important thing first
  • if yes - go fight as violent as you want

[2023-05-25 Thu 19:27] %

53. loading context of an ongoing project

to take up the task from last time, either:

  • have a global picture where the previous work is visible and it is self-evident how they should be processed(the vision is clear)
  • GTD task traking
  • for some knowledge work, it is hard to have precise task definition. Therefore, a mangeble-sized workspace inside a more general GTD task may fit usage
  • project zettelkasten
  • navigation/index note

54. Brian train - studying for success by Richard Palmer and Chris Pope

IT’s an practical book. I looked the menu, and saw some insights that looks really delicious [2023-06-04 Sun 18:30] Sweller et al. - 2019 - Cognitive Architecture and Instructional Design 2.pdf: Page 1

55. emacs keyboard macro don’t include function call with input prompt

[2023-06-05 Mon 16:52]

56. abstraction higher than NN

I want to be working on an abstraction level higher than ANN so I could incorporate ANN, SNN and other stuff, and be doing the definition/idea rather than technique [2023-06-07 Wed 10:40]

57. Confidence is self-contained   blog

[2023-06-14 Wed 16:16]

def of confidence
a lot, but they try to describe a common feeling that occurs when man’s flesh and soul are in the same place
  • feeling/consciousness of one’s power
  • feeling/consciousness of reliance on one’s circumstances
  • belief that one will act in a right/proper/effective way

The effect and existence of confidence is self-contained

57.1. existence :: Confidence don’t depend.

…Or rather, don’t depend on anything else than you yourself. As you are always with yourself, it’s dependency is resolved always.

57.1.1. confidence <-x– success

The key imagined enemy of this property is that people tends to think that confidence is based on success:

  • “I’m not confidence because I have no portofolic to showcase”
  • “I’m not confidence because I’m not doing what I think I’m supposed to do”
  • “I’m not confidence because I have some defects, I procrastinates, I’m an addict, I’m not smart…”
  • “I’m not confidence because I failed before”

A joke would be that, if confidence is key to success, then you would need it to succeed in anything, but then you’d need some success to be confident, for which you have to be confident first… It’ll be classical Egg or Chicken first problem. One way to argue aroudn the problem is taking baby steps, build a streak of confidence from stuff you just can’t fail.

Another way around it, is to hold confident to be self-contained as your premise. Under which you would discover that the success story you based your confidence on is not a support, a stand to hold you higher, but rather a rope, a lease that give you a reason to be dragged down.

57.1.1.1. it’s not true anyway

You can never suggest that because you succeeded before, you would succeed again, even with exactly same subject. Prediction of success can only stand on reality rather than history, and assuming that the envoirnemnt of reality stayed the same is a bet with high risk.

57.1.2. options: [confidence, no confidence]

You can never be sure if you are doing the right thing, or if you have any power, or if you are doing the thing the right way: you just can’t. The world is infinitive, and you don’t get it right forever. But you can do something, you do have/sure are something, you can do the thing some way:

And you can do it with confidence, or you can do it without confidence. – Heramn He

It’s purely your choice.

57.2. effect :: Confidence is always better.

It at least do something, and it feels good.

57.2.1. Confidence never backfire

It’s dumb, but worth saying: believing in yourself can backfire at you in no way. If something do, it’s arrogance, not crediting others, ignoring the reality, or being actually not confident, but acting like you are.

57.2.2. All the goods it can do

  • you don’t back out
  • you don’t wonder about asking yourself “should I be doing this?” “do I belong here?” all the time
  • easier focus, which is hard to couple with, but is coupled here with
  • easier self-consciousness
  • easier to love(both to the stuff you do and your co-workers)
  • happier
  • more relax, which leads to
  • more creativity
  • generally it’s just beautiful

57.2.3. Acting and Practicing Confidence

The thing about acting like having confidence is that believing in yourself and believing that you are confidence is actually quite different, though would look the same.

believing in yourself
discussed above, totally free cash kind of thing
believing that you are confidence
the issue is the common superficial stuff. The actual thing you’d be practicing would be, though similar, something other than confidence, and their property would be unknown.

57.3. Little practices you could do

57.3.1. Discrediting success

Think about it, and in your way state how success is not even close to be root of confidence. With enough attention to it you could deconstruct your old habit of that success-confidence correlationship. Sub-conscious cue-responses for them would stick long, but you can just easily overwrite them by attending to them consciously.

It’ll just be a stupid mistake to laugh about rather than an identification crisis to die over.

57.3.2. “Do it again, but this time with more confidence”

It’s a practice I read somewhere, and I can’t recall where exactly, (I think from a youtube discussion video kind of thing) where you do something with explicit condition that you are going to do it more confidently.

I think it’s a great exercise because you are more familiar with the subject and can focus more on being confident, and it’s a bite-size exercise with no pressure like “I have to keep this all day or I’m doomed” which is surprisingly common.

57.3.3. “I …… , and I’m confident about that”

Example would be: “I’m exploring rabbit holes in programming, and I’m confident about that.”

The logistic behind this exercise is that:

  • first, I do it a lot when I get the confident feeling. Kind of like gravity pull or warm up that give you an instance dose of confidence
  • you may be feeling exhausted or depressed when “jumping rabbit holes”, that’s time you don’t feel confident, and with the exercise you could just reprogramme that.
  • plus you get practical feeling of confidence free of any effort. What’s it going to be like if you are confident when exploring the rabbit holes? Now you know, and you don’t have to “be aware of confidence before starting working and keeping mental track of it”. When you think of it, just pick a thing you just done and practice this.

58. secondary dominant give reason to bring notes outside the tone in

exotic sound. [2023-06-26 Mon 00:01]

59. Scales give sound relative to the key

on C, Dm7 give a dorian sound. The Dorian sound on D converge to the C major scale, the C majorness [2023-06-26 Mon 00:14]

60. Transcription

  • don’t write it down: it is how they played it that matters, it is how you heard them that you recall in a session.
  • use your ear. audio clip to copy from is best. [2023-06-26 Mon 15:45]

61. how I practice piano

  • I’ll have a book of techniques. a technique library
  • when I want to abtain a technique, I add it to my practice diet, with specific “what to practice(content of practice)” and “outcome”(where I remove it from the practice diet)
  • in each practice session(I’ll set default at 30minutes), focus on getting a small portion of the technique right and instinctive, make myself familiar with it and use them flexibly. revisit it very soon, cycle on small subsets of it
  • from time to time, assess the practice diet, and discard already familiar technique and add new technique I’v seen and is interested at but don’t have time for it before

[2023-06-26 Mon 00:15]

62. org-roam link behave weirdly when is in definition list

in the following heading, when Samsonovich :: xxxxxx is followed, would open a buffer *select-link* in help mode. Removing :: from the description would remove the behavior

62.1. relevent note files

records an idea: degree of freedom in control system and similar idea in intelligence

  • 1 categorization: spike-based NN and artificial NN.
  • task theory stub
  • what is neuro-symbolic?
    guess
    symbollic
    use symbol representation of world, rules, logic and reasoning in the AI system. wiki
    neuro
    neuro network
    why deep learning looks intelligent
    human have a builtin function approximator in brain, system 1, as categorized in thinking fast and slow by daniel kahneman
    (no term)
    I read a few articles
    [[reference/samsonovichSociallyEmotionalBraininspired2020.org][Samsonovich
    Socially Emotional Brain-Inspired Cognitive Architecture Framework for Artificial Intelligence]] an architecture
    [[][Sweller, van Merriënboer, Paas
    Cognitive Architecture and Instructional Design: 20 Years Later]]

df

[[reference/samsonovichSociallyEmotionalBraininspired2020.org][Samsonovich
Socially Emotional Brain-Inspired Cognitive Architecture Framework for Artificial Intelligence]] [2023-06-28 Wed 20:34]

63. chime used in the early part is amazin

That is work from crashed by empty sky [2023-06-29 Thu 11:51]

64. human-like agent with intrinsic autonomy

64.1. kernel-based learning paradigm

it takes some kind of a kernel, like a randomized ANN, or a trained ANN, or a written cognitive architecutre agent. It’ll combine the kernel with some kind of motivation system(Sun, Clarion)(I could abstract this to make a specificatoin of kernel-based-compliant motivation system), and allow it to develop/scale in it’s own representation, like in program text in cognitive architecture or in nodes in ANN.

I haven’t think much about what it can do or could be evaluated. This is from my observation development of man’s idea, that is they have, from sometime, a relatively small set of ideas, which they used, through some kind of reasoning(the ideas and reasoning would combine to be the kernel), and some kind of motivation, to expand on its own.

The next step of this could be more research into motivation systems, both as they present in intelligence and as they are implemented (like Clarion Project), and try adapt it with a broader and more abstract kernel definition. I’d imagine very many times of iterations in trying to establish a kernel definition of this sort, and articulate that motivation system specification. Existing work may help, like Clarion sort of implemented a motivation system, and it seems to be a major aspect their team focus on (I saw multiple publications on that) so there’s some concrete code I could look at.

The morale of this is that I think if a mechnism could be cornerstone for something, they as long as its implemented somehow (in an symbolized manner), the “something” would be achieved, in this context an agent with intrinsic autonomy(which I’d say in turn would be one cornerstone of AGI). But it would still be limited by the kernel.

64.2. unified representation that allows logic reasoning, representation of experience, networked thinking, shift of reasoning paradigm, focus, and simulation

The next step I’d want to be doing is to develop a representation like this. Maybe I could do it with some modification to ANN, or even a particular configuration of ANN(like a node of this representation would be a 20 neuro ANN connected somehow).

The sole purpose of this is to create a kernel for the above learning scheme that supports simulation of experience(Bach), and adaptionist(Wong) reasoning at once. Others I add because I like them. The kernel should be able to modify it self to achieve all the required mechnism for an human-like general intelligence somehow. The list is yet to be clear, so that could be another starting point.

The unified part of it is essential. That imply total autonomy without any human interference (other than illustration and providing input). One analogy I just thought of is LISP: with a handful of special forms, you can create any program in almost any language with LISP(I could imagine myself doing it with a macro as a parser translating in-line java code in LISP). If a LISP program could rewrite itself it could just became everything. The structure of LISP is quite unified, which allow writing part of the language in itself as well as such very powerful polymorphism, that only the most basic editing, that is adding symbols using only the language’s facility, could lead to almost everything. Supreme expressivity.

The representation I’m thinking would be less powerful, but I’d work to that kind of degree of unity.

64.2.1. sensory inputs

It could be a variable part.

64.3. AGI

AGI, or a form of it I’d articulated as human-like agent with intrinsic autonomy, in my idea could be achived with simulation + adaptionist reasoning + motivation + kernel development. This statement may need modification, but with these mechnism implemented, such agent should be able to run by itself with absolutely no human interference, and develop/behave in a human-like manner, with an upper limit partially dependent on the size of representation. (partially on the power of it – like ANN)

64.4. The math

ANN is a math expression. The power of an ANN relies on how many different ways of influence it knows beforehand, so it could take them into account in the later gradient decent part, and find the optimized composition of influence with regard to the training data.

In very much similar way, the learning scheme described above would be an architectural expression, the power of which relies on how many different mechnisms it could simulate/create easily(as adaptionist reasoning is present) with basic facilities. It may require definition of a new form of calculus/logic to articulate, like what NARS did.

64.5. next steps

  • check out various samples of motivation systems and kernels
  • check out learning theory to figure out basic elements properties of a learning algorithm and a learnable data structure/concept
  • chekc out various learning techniques to try to draw analogy about how kernel should expand itself. (transformer….and others)

65. how unified structure are going to build different strucutre and hierarchy

66. discipline

discipline is a way of organising ideas and theories, as well as research object like neuro circuit.

Like other organisations, disciplines would overlap, and can be quite arbitary

67. neural network as policy

[2023-07-29 Sat 22:37]

  • policy is a map from state to action (as defined in Markov decision policy)
  • neural network can be abstracted to a map from a vector to a vector
    • input vector as the state
    • define the choice of action on the output
  • –> neural network map state to action
  • –> neural network as a representation of the policy
    • other representation model: desicion tree…

Author: Linfeng He

Created: 2024-04-05 Fri 02:23