hereditary inequality

Umur median warga kini 31 tahun. Amat cantiklah kebelakangan ini, ramainya mampu mengulas dasar perundangan persekutuan, dan bakal menjadi penggubal undang2 yang kurang remeh daripada puak YB dulu2.

Hakikat 1 : Malaysia dirikan dalam keadaan ketidaksamarataan ekonomi

Hakikat 2 : dasar ketidaksamarataan turun-temurun merupakan langkah perundangan yang kekok dan telah membawa kepada ketidakstabilan politik sampai hari ini

Entahlah ke mana nanti, kedukaan sebangsa Malaysia.

ngapo cina xsuka beli ngan melayu?

Pendek cerita, pridatang yang lahir lepas merdeka anggap dirinya diperhambakan seumur hidup. Jadi naiklah budaya x jaga x, y jaga y. Ini termaktub dalam perundangan. Jadi kena sampai zaman depan baru perubahan perundangan boleh hapuskan kedukaan sebangsa malaysia sekaligus.

 Itu pandangan saya mengenai orang ramai, bukan pendirian saya

deference to authority

Well, the problem here is the stagnant Malaysian mentality of "I vote in an authoritarian leader who will make the change I want" instead of "I will directly pressure any leader to make the change I want."

breadth of experience

I took a stroll to the post office, and thought about why I have been think about my friends from the 90s.

One salient point was that many of them developed traits of increased insecurity and gatekeeping over a period of about 8 years, between the late 90s and early 00s. Perhaps that is what the transition from adolescence to young adulthood centres on, for many people.

I have had different traumas of course, so my ambitions appear to be rather different. I lack the concern that there are tables I am not invited to - in fact often I am bemused that I even get invitations to sit with people whom I don't seem to be helping at all. I am mainly concerned with the quality of my own table, and the detraction of quality brought about by those I bring to it. Then again perhaps it is just a matter of taste, and we differ in that respect.

I think, one of my greatest challenges has been, context switching - i. e., memory management. When engaged in communication and service to society, I prefer to be wholly present in order to work within the complete frame-of-mind of the people I am helping. But outside of that context, I prefer to be wholley absent in order to work around them. 

This is not something that many people aspire to. They often consider it mean. I think, it is a joy to participate in the lived experiences of other people, and then also to be able to scorn them immediately as required by circumstances. The development of such breadth of capability is what I think of as mental conditioning. 

bahasa rojak

However, they tied language to race, and race to money, so too bad ... kedukaan sebangsa malaysia

I summarised AI for my dad

/ I Summarised AI for my Dad /

( An improvement on my prior understanding)

Current mainstream AI modelling :

0 input text is converted to a "token" sequence from the model's vocabulary

1 so we begin with a sequence of tokens

2 the model understands tokens as being locations, in a N-dimensional space : so each token is simply stored as an N-space coordinate "vector" 

3 then the model finds relationships, between each token ( in the input sequence ), and every other token ( in the input sequence ) : it consults a database of relationships learnt during training, and also accounts for the order of tokens in the sequence 

3.1 the database of relationships can be subdivided into chapters, so that each chapter focuses on different types of relationships

3.2 this step is computationally parallelisable, therefore you can crunch a token sequence of length 5 and length 5000 in nearly the same time, if you have 1000x the hardware

3.3 this step outputs a sequence of "enriched vectors" i.e. each token is now represented by a more contextualised location in N-space

4 each "enriched vector" is then subject to a select subcomittee; the whole step produces a sequence of "committee enriched vectors" 

4.1 again, execution is parellisable 

3 & 4 : both the database of relationships between tokens, and subcommittee processes are learnt by trial&error during the model's training

5 the entire [ 3 & 4 ] operation is called a layer, and current models are 80 to 120 layers deep ; this sequential process is what enables logical branching to occur

6 after [ 3 & 4 ], are executed 80 to 120 times, a single "highly enriched vector" representing a unique location in N-space is produced ... and this is finally used to predict ONE NEW TOKEN to be appended to the input token sequence

7 the model then uses the [ input tokens + new token ] and runs back to step 1, and it keeps doing this until step 6 says "no more token are recommended" 

8 finally, [ all the new tokens ] are translated back into text