Comment by staticshock

No idea why you were dv'd.

It still takes roughly nine months to make a human baby, regardless of how many women or babies are involved!

It seems overly pessimistic about education. Book learning isn't everything, but a physics textbook could be seen as the compression of centuries of experience.

I don't know. Growing up and seeing life and people around me I firmly believe that if you have enough brain power and intuition for $TOPIC you can speed-run it. At the same time, with time and experience and doing/re-doing it, you will learn or master $TOPIC [1] even with less brain power.

[1] Depending on the topic and the level of knowledge of it.

There clearly is though. You don’t remember every detail of every moment that constitutes the experience.

Some examples.

Firstly, Twitter has an upper bound on the complexity of thoughts it can carry due to its character limit (historically 180, now somewhat longer but still too short).

Secondly, a biased or partial platform constrains and filters the messages that are allowed to be carried on it. This was Chomsky's basic observation in Manufacturing Consent where he discussed his propaganda model and the four "filters" in front of the mass media.

Finally, social media has turned "show business [into] an ordinary daily way of survival. It's called role-playing." [0] The content and messages disseminated by online personas and influencers are not authentic; they do not even originate from a real person, but a "hyperreal" identity (to take language from Baudrillard) [0]:

    You are just an image on the air. When you don't have a physical body, you're a
    _discarnate being_ [...] and this has been one of the big effects of the electric age. It
    has deprived people of their public identity.

Emphasis mine. Influencers have been sepia-tinted by the profit orientation of the medium and their messages do not correspond to a position authentically held. You must now look and act a certain way to appease the algorithm, and by extension the audience.

If nothing else, one should at least recognize that people primarily identify through audiovisual media now, when historically due to lack of bandwidth, lack of computing and technology, etc. it was far more common for one to represent themselves through literate media - even as recently as IRC. You can come to your own conclusions on the relative merits and differences between textual vs. audiovisual media, I will not waffle on about this at length here.

The medium itself is reshaping the ways people represent, think about, and negotiate their own self-concept and identity. This is beyond whatever banal tweets (messages) about what McSandwich™ your favourite influencer ate for lunch, and it's this phenomena that is important and worth examining - not the sandwich.

[0] Marshall McLuhan in Conversation with Mike McManus, 1977. https://www.tvo.org/transcript/155847

It's confusing because "message" is not using its lay meaning, and decades of "medium" and "media" meaning drift meant that it isn't either.

For "the medium is the message", "medium" refers to any tool that acts as an extension of yourself. TV is an extension of your community, even things like light bulbs (extends your vision) are included in his meaning.

McLuhan argued that all forms of media like that carry a message that's more than just their content. "The message" in that argument refers to the message the medium itself brings rather than its content. For example, the airplane is "used for" speeding up travel over long distance, but the the message of its medium itself is to "dissolve the railway form of city, politics, and association, quite independently of what the airplane is used for."

You can see it happening via online media that extend ourselves across the internet. Think of how, once easy video creation via Youtube became uniform, web comics stopped becoming a popular medium for comedy online. It's not like the web comics faded because they got worse; it's that they faded into a niche format because people didn't want to communicate via static images anymore. Or how, once short form videos on TikTok got big, you saw other platforms shift to copy the paradigm. McLuhan's point is that it's not just the content of those short form videos that matters; it's the message of the format itself. Peoples' attention spans grow shorter because of the format, and before too long, we saw the tastes and expectations of the masses change. Reddit's monosite-with-subcommunities format and dopamine triggering voting feedback mechanism were its message more than any actual content posted there, and it's why traditional forums are niche and dwindling.

If you want to get a pretty good understanding of it, just read the first chapter from his book Understanding Media. It's short and relatively straight forward.

Yes. The main problem is that they can only lead you to familiar territory. The next problem is that it's hard to notice when you are back where you started.

This has been my main struggle using LLMs to soundboard my new idea. They can write an eloquent interpretation of the entire concept, but as soon as we get to implementation, it stumbles right into creating the very system I intend to replace.

So I would say it's the other way around: LLMs are an excellent map, but a terrible compass. Good enough if you want to explore familiar territory, but practically unusable on an adventure.

That's a feature that could be implemented by a subjective framework.

Traditionally, we use definition as the core primitive for programming. The programming language grammar defines the meaning of every possible expression, precisely and exhaustively. This is useful, because intention and interpretation are perfectly matched, making the system predictable. This is the perspective of objectivity.

The problem with objectivity is that it is categorically limited. A programming language compiler can only interpret using the predetermined rules of its grammar. The only abstract concepts that can be expressed are the ones that are implemented as programming language features. Ambiguity is unspeakable.

The other problem is that it is tautologically stagnant. The interpretation that you are going to use has already been completely defined. The programming language grammar is its own fundamental axiom: a tautology that dictates how every interpretation will be grounded. You can't choose a different axiom. Every programming language is its own silo of expression, forever incompatible with the rest. Sure, we have workarounds, like FFIs or APIs, but none of them can solve the root issue.

A subjective perspective would allow us to write and interpret ambiguous expression, which could be leveraged to (weakly) solve natural language processing. It would also allow us to change where our interpretations are grounded. That would (weakly) solve incompatibility. Instead of refactoring the expression, you would compose a new interpreter.

Because code is data, we can objectify our interpreters. We can apply logical deduction to choose the most relevant one, like a type system chooses the right polymorphic function. We can also compose interpreters like combinators, and decompose them by expressing their intentions. This way, we could have an elegant recursive self-referential system that generates relevant interpreters.

Any adequately described algorithm or data structure could be implemented to be perfectly compatible with any adequately interpreted system, all wrapped in whatever aesthetics the user chooses. On the fly. That's the dream, anyway.

That's always been a fun idea. Even a thousand years ago, when most people couldn't read or write, we yearned for more. Even without a description of the problem and its domain, it's immediately obvious that perfect communication would be magic.

The problem is that it's impossible. Even if you could directly copy experience from one mind to the other, that experience would be ungrounded. Experience is just as subjective as any expression: that's why we need science.

> through the culture war (nobody can define "man" or "woman" any more, sometimes the word "man" is used to refer to a "woman," etc).

That's a pretty mean rejection of empathy you've got going on there. People are doing their best to describe their genuine experiences, yet the only interpretations you have bothered to subject their expression to are completely irrelevant to them. Maybe this is a good opportunity to explore a different perspective.

> LLMs just accelerate this process of severing any connection whatsoever between signified and signifier.

That's my entire point. There was never any connection to begin with. The sign can only point to the signified. The signified does not actually interact with any semantics. True objectivity can only apply to the signified: never the sign. Even mathematics leverage an arbitrary canonical grammar to model the reality of abstractions. The semantics are grounded in objectively true axioms, but the aesthetics are grounded in an arbitrary choice of symbols and grammar.

The words aren't our problem. The problem is relevance. If we want to communicate effectively, we must find common ground, so that our intentions can be relevant to each others' interpretations. In other words, we must leverage empathy. My goal is to partially automate empathy with computation.

Non-determinism is not as much of a problem as the lack of spec. C++ has the C++ norm, Python has its manual. One can refer to it to predict reliably how the program will behave without thinking of the generated assembly. LLMs have no spec.

"You can’t treat a prompt like source code because it will give you a different output every time you use it"

But it seems we are heading there. For simple stuff, if I made a very clear spec - I can be almost sure, that every time I give that prompt to a AI, it will work without error, using the same algorithms. So quality of prompt is more valuable, than the generated code

So either way, this is what I focus my thinking on right now, something that always was important and now with AI even more so - crystal clear language describing what the program should do and how.

That requires enough thinking effort.

It's staggering to me how many times I've heard this argument that LLMs are just the next level of abstraction. Some people are even comparing them to compilers.

> AI coding isn’t an abstraction

Isn't it an abstraction similar to how an engineering or product manager is? Tell the (human or AI coder) what you want, and the coder writes code to fulfill your request. If it's not what you want, have them modify what they've made or start over with a new approach.

> There are skills we're losing that are probably ok to lose (e.g. spacial memory & reasoning vs GPS, mental arithmetic vs calculators)

I'd argue these are not at all OK to lose. You live in an earthquake zone? You sure better know which way is north and where you have to walk to get back home when all the lines are down after a big one. You need to do a quick mental check if a number is roughly where it should be? YOu should be able to do that in your head.

There might be better examples that support your point more effectively e.g. cursive writing

> "not doing cognitive push-ups leads to cognitive atrophy" This is one of the points being made in the post, at least in reference to people who already have some mastery of their craft. If they outsource their thinking without elevating it, they aren't exercising that metaphoric muscle between their ears.

Are compilers deterministic?