I understand a lot of complex things, maybe because I spent my whole life trying to understand and explain things around me, since 4 year old, when I used no name every single car on the road in a small Ukrainian Steel and mining town where I was born. Understanding cannot be “outsourced” or even safely “delegated”. One will always end up with a sort of “tragedy of commons”, when sterilization and modern technologies produced packaged foods which slowly but surely kill you. This is what happens when you “delegate” your own understanding. ...

The most difficult thing with the markets is not to take sides, even the rational one, and to never push against the current sentiment, however idiotic it may be. These three popular movies about “the insides of the financial markets” have conditioned lots of people in a wrong way, by presenting a naive, grossly oversimplified, but “seemingly fair” view, and distorted one’s perception of reality. Yes, these are all ponzis and yes, the market participants “have to do something” to earn their living, and institutions to roll on, until they become Lehman Brothers. ...

So I watched some. The launch video I mean. Closed the frame when they began that “voice” thing. The PhD. level across all subjects is just a meme. I can easily be shown by asking the question that require a beyond memorizing textbooks reasoning. I don’t want to “register” for “Grok4”, but here are some example problems which will break the “PhD level” meme. A recursive functions in, say, Ocaml, or Scala, without explicitly mentioning the accumulator pattern as the required way to avoid stack overflows on languages which does not do TCO at the compile time. This is very basic stuff, which all “PhDs” have to know. The inner lambda with an extra argument, and the “trampoline” is such a classic pattern that some compliers do it automatically. Again, without mentioning it the model will fail by writing non TCO code . ...

There is a very simple trick to break the illusion and to see through “the veil of Maya”. Locally-run models, like Deepseek-R1-14b-0528 (at full fp16 quantization), which is the best I could have, produce vastly different “answers” for exactly the same prompt not just between two runs, but if one uses a different math library stack (like recompiling with forcing Intel MKL). Every time we run a prompt a reasonably good model spits out something which “looks very reasonable”, (unless your are an actual expert in the field), because it captures “common sense”, expressed in the training data. ...

Just a few years ago we had that running joke “pasting code from stackoverflow”, which describes a coder, who just find and copy-paste the code – the “right” answers – without any understanding whatsoever. It is well-understood at the level of cognitive neuroscience, that skipping the part of “doing it yourself” (and so never getting these necessary 10,000 hours of a deliberate practice) basically makes us dumber (lots of supporting MIT studies, google them) and ultimately wastes out time, the only irreplaceable and the most valuable resource we ever had. ...

Lets “solve” programming (once again, LOL), in a couple of pages, simply because why tf not. and to put the LLMs and their shills and worshipers into shame (yes, yes, I know, they do not have any). We will build a simple abstract and general “meta-theory”, which is, like a religion grounded on Buddha’s compassion, provide a foundation of peaceful and cooperating traditions, which guide people in their decision making in a overwhelmingly complex Reality by providing easy to understand and easy to apply “heuristics” or “rules of thumb”. ...

DESCRIPTION: It is over. It is that simple. It explains almost everything correctly. This is just another way of saying that familiarity and 10,000 hours of practice are not optional. The best books about trading the stock market has been published before the dot-com bubble, in the late 90s, driven by the emerged opportunities of computerized trading (using dial-up modems to download the data and to access the broker). People who were familiar with trading back then and have had enough experience were prepared to participate in the crapto craze, while “we” have to learn anything on the go, under a tremendous emotional and cognitive pressure, and fail, because we didn’t know what information is relevant and what signals are meaningful, along with the lack of solid trading practices. It is that simple. ...

Given the US govt. security agencies recommendations for using Memory Safe Languages (as if there is more than one!), let’s bootstrap the right understanding of what the “memory safety” means from the first principles. The “first principles” will be indeed the first ones, because we will go all the way back to the underlying recurring patterns in What Is, from which the fundamental mathematical notions have been captured, properly generalized, abstracted away, named and their properties systematically studied. ...

An intuitive understanding – approximate, imprecise but not wrong in the principles. A level of vague abstractions which capture the right underlying relationships – nothing essential is missed, nothing imaginary and non-existent is added. Everything “just naturally follows” from (can be explained by) the “right [intuitive] understanding”. This is what our ancient ancestors used before they have evolved the “scientific method”. Almost everything, however, can be “explained” (to a fool) by an arbitrary super-natural make-believe nonsense, so we have to be very suspicious to what the “talking heads” are saying and question everything. ...

Reading Rust theads on /g/ is an endless source of astonishment . We live in the age of enshitffication of knowledge and even information, where literal genens are obsessed with emotionally charged narratives about make-believe problems. Anyway, whatever. The real and fundamental innovation behind Rust is this. The great well-educated by studding the underlying principles of everything around them “old-timers”, like Joe Armstrong (R.I.P.), discovered the mathematical /fact that sharing and mutation cannot coexist in principle. The fundamental mathematical property of “referential transparency” is necessary to make any guarantee about the correctness of a program. The notion is that everything is an expression and any expression is “pure”, and only denotes a value (to which it can be eventually reduced or evaluated to. Thus, any expression can be substituted by a value it denotes (eventually evaluated to) without changing the meaning (semantics) of the any other expression within a program. This is the essence of functional programming, and it is a fundamental property of all correct programs. ...