I'm an older millennial, probably one of the last generations who was formally taught that organizations like the New York Times and CNN were authoritative, bibliography-worthy sources of information due to their reputation and standards. I haven't cared much about what either outlet has produced in years. For every good investigative piece there's a mountain of obvious propaganda or refusal to cover topics they find uncomfortable with any objectivity.

The signal to noise ratio is so low, why pay attention? There's a lot of bad takes on twitter and non-mainstream media (to put it mildly) but it at least makes me aware of more things.

Right. The skeptical newer generation knows better. It's the generation that is immune to influence. They're so resistant to it that they've finally driven advertisers to realize that spamming YouTube, IG, TikTok, with ads peddling some new hype every week is pointless.

Sarcasm aside, the newer generation, in any generation, is always as naive as they're said to be. You're not born with wisdom and your parents can't save you from the candle fire, no matter how much they try. Sooner or later, you'll have to burn that finger to learn. Life is an experience game. No way around it.

Yes. And then they turn around and trust that the Boston Marathon Bomber was some random kid because Reddit said so.

The new generation of netizens distrusts classic media and then suddenly trusts Reddit and Google searches and random blogs.

Bad Twitter arguments citing YouTube videos talking about a Redditors problem about Microsoft Updates and SSDs just broke through a week or two ago and nearly everyone involved in the discussion is utterly wrong.

Laughs in Polish GenZ voting for Konfederacja (alt-right)

Of boomer propaganda. But don't worry, as voters evolve, so does propaganda.

- Use the AI and ask for answers. It'll generate something! It'll also be pleasant, because it'll replace the thinking you were planning on doing.

- Use the AI to automate away the dumb stuff, like writing a bespoke test suite or new infra to run those tests. It'll almost certainly succeed, and be faster than you. And you'll move onto the next hard problem quickly.

It's funny, because these two things represent wildly different vibes. The first one, work is so much easier. AI is doing the job. In the second one, work is harder. You've compressed all your thinking work, back-to-back, and you're just doing hard thing after hard thing, because all the easy work happens in the background via LLM.

If you're in a position where there's any amount of competition (like at work, typically), it's hard to imagine where the people operating in the 2nd mode don't wildly outpace the people operating in the first, both in quality and volume of output.

But also, it's exhausting. Thinking always is, I guess.

[0] Rijnard, about https://sourcegraph.com/blog/how-not-to-break-a-search-engin...

You don't have to remember everything. You have to remember enough entry points and the shape of what follows, trained through experience and going through the process of thinking and writing, to reason your way through meaningful knowledge work.

If humans did not have any facilities for abstraction, sure. But then "knowledge work" would be impossible.

You need to remember some set of concrete facts for knowledge work, sure, but it's just one—necessary but small—component. More important than specific factual knowledge, you need two things: strong conceptual models for whatever you're doing and tacit knowledge.

You need to know some facts to build up strong conceptual models but you don't need to remember them all at once and, once you've built up that strong conceptual understanding, you'll need specifics even less.

Tacit knowledge—which, in knowledge work, manifests as intuition and taste—can only be built up through experience and feedback. Again, you need some specific knowledge to get started but, once you have some real experience, factual knowledge stops being a bottleneck.

Once you've built up a strong foundation, the way you learn and retain facts changes too. Memorization might be a powerful tool to get you started but, once you've made some real progress, it becomes unnecessary if not counterproductive. You can pick bits of info up as you go along and slot them into your existing mental frameworks.

My theory is that the folks who hate memorization are the ones who were able to force their way through the beginner stages of whatever they were doing without dull rote memorization, and then, once there, really do not need it any more. Which would at least partly explain why there are such vehement disagreements about whether memorization is crucial or not.

While the article makes some reasonable points, this is too far gone. You don't need to know how to "weigh each minute spend on flexibility against the minutes spent on aerobic capacity and strength" to put together a reasonable workout plan. Sure, your workouts might not be as minmaxed as they possibly could be, but that really doesn't matter. So long as the plan is not downright bad, the main thing is that you keep at it regularly. The same idea extends to nearly every other domain, you don't need to be a deep expert to get reasonably good results.

I think there are at least two models of work that require knowledge:

1. Work when you need to be able to refer to everything instantly. I don't know if this is actually necessary for most scenarios other than live debates, or some form of hyper-productivity in which you need to have extremely high-quality results near-instantaneously.

(HN comments are, amusingly, also an example – comments that are in-depth but come days later aren't relevant. So if you want to make a comment that references a wide variety of knowledge, you'll probably need to already know it, in toto.)

2. Work when you need to "know a small piece of what you don't remember as a whole", or in other terms, know the map, but not necessarily the entire territory. This is essentially most knowledge work: research, writing, and other tasks that require you to create output, but that output doesn't need to be right now, like in a debate.

For example, you can know that X person say something important about Y topic, but not need to know precisely what it was – just look it up later. However, you do still need to know what you're looking for, which is a kind of reference knowledge.

--

What is actually new lately, in my experience, is that AI tools are a huge help for situations where you don't have either Type 1 or Type 2 knowledge of something, and only have a kind of vague sense of the thing you're looking for.

Google and traditional search engines are functionally useless for this, but asking ChatGPT a question like, "I am looking for people that said something like XYZ." This previously required someone to have asked the exact same question on Reddit/a forum, but now you can get a pretty good answer from AI.

It’s the same with a lot of other things. AI and search engines help a lot but you are at an advantage if at least you have some ability to gauge what should be possible and how to do it.

If you never memorize anything, but are highly adept at searching for that information, your brain has only learned how to search for things. Any work it needs to do in the absence of searching will be compromised due to the lack of conditioning/experience. Maybe that works for you, or maybe that works in the world that's being built currently, but it doesn't change the basic premise at all.

“Try to learn something about everything and everything about something.”

Then the internet came, and we asked the internet. The internet wasn't correct, but it was a far higher % correct than asking a random person who was near you.

Now AI comes. It isn't correct, but it's far higher % correct than asking a random person near you, and often asking the internet which is a random blog page which is another random person who may or may not have done any research to come up with an answer.

The idea that any of this needs to be 100% correct is weird to me. I lived a long period in my life where everyone accepted what a random person near them said, and we all believed it.

Concepts have to be "internalized" into intuition for much of our thinking, and if they are externalized, we become a meme-copy machine as opposed to a thinking machine.

[1] https://en.wikipedia.org/wiki/Rules_for_the_Direction_of_the...

> To find what you need online, you require a solid general education and, above all, prior knowledge in the area related to your search. > > [...] > > If you can’t produce a comprehensive answer with confidence and on the whim [...] you don’t have the sufficient background knowledge. > > [...] > > This drives us to one of the most important conclusions of the entire field of note-taking, knowledge work, critical thinking and alike: You, not AI, not your PKM or whatever need to build the knowledge because only then it is in your brain and you can go the next step. > > [...] > > The advertised benefits of all these tools come with a specific hidden cost: Your ability to think. [This passage actually appears ahead of the previous one–ed.]

This is best read alongside: https://news.ycombinator.com/item?id=45154088

But online? @grok is this true?

That article articulated the reason slightly differently, arguing you need to hold multiple concepts in your head at the same time in order to develop original ideas.

Still, I'm not sure you have to remember everything, but I agree you have to remember the foundational things at the right abstraction layer, upon which you are trying to synthesize something new.

Fitness guidelines is very much not a settled science, and is highly variable per individual beyond the very basics (to lose weight eat fewer calories than you burn, to build muscle you should lift heavy things).

For every study saying that 8-12 reps x3 is the optimal muscle growth strategy there is another saying that 20x2 is better, and a third saying that 5x5 is better. If you want to know how much protein you should eat to gain muscle mass, good luck; most studies have settled on 1.6g/kg per day as the maximum amount that will have an effect, but you can find many reputable fitness sources suggesting double that.

You can memorize "facts", but they will change as the state of the art changes... or is Pluto still a planet?

The ability to parse information and sources, as well as knowing the limits of your knowledge is far more important than memorizing things.

"In knowledge work the bottleneck is not the external availability of information. It is the internal bandwidth of processing power which is determined by your innate abilities and the training status of your mind."

I’ll say this: between store, search, synthesize and share, store and synthesize are consistently the most difficult to nail down.

A society that wishes to succeed in creating an activated and knowledgeable populous should be interested in how to train people to notice better, and to create insightful follows.

In the words of David Deutsch (paraphrasing): knowledge consists of conjecture and error correction

> “I just ask ChatGPT for that, too!”, the AI generation might ask. Ok, and then what? How can you assess the answers … you are taking on an impossible task, because you can’t use enough of your brain for your cognitive operations.

So it’s Zeno’s paradox of knowing stuff?

It can’t be impossible to know things, you’ve just got to decide when you know enough to get going on. Otherwise you’re mired in analysis paralysis and you never get anything done.

I do agree that deep knowledge of the foundations a subject - particularly a skilled practice or craft - is a path to proficiency and certainly a requirement for mastery. But there are plenty of times when you can get away with ‘just reading the documentation’ and doing as instructed.

You do not first need to invent the universe in order to begin exercising, you can just start talking a 20 minute walk after lunch.

I would say your own knowledge is like a memory cache. If you know stuff, then the relevant work becomes order of magnitudes faster. But you can always do some research and get other stuff in the cache.

(Human mind is actually more than a cache because you also create mental models, which typically stay with you. So it's easier to pickup details after they get evicted, because the mental model is kept. I think the goal of memorising stuff in school should be exactly that - forget all the details, but in the learning process build a good mental model that you have for life.)

Memory is helpful but brains aren’t hard drives, they aren’t designed to store information perfectly.

That said AI, Search and the like can be quite useful and helpful.

Insisting that people know exercise physiology to work out is a bit much. That's what trainers and coaches are for. Now drop and give me twenty.

The real problem with LLMs remains that they can't really do the job of thinking yet, because they're wrong too often. They can both hallucinate and get lost. What the AI situation will be in five years, we don't know.

My experience as a bit of geek is it's easy to get caught up in theory and do stuff that doesn't work in practice. Better than either the LLM or theorising is an experienced coach who can look at what you are doing and say don't to that - it's all wrong - do this etc.

When you're writing, you can often take your time. Too little knowledge, though, and it will require a lot of homework.

1- You may remember only the initial state and the brain does the rest, like with mnemonics

2- You may remember only the initial steps towards a solution, like knowing the assumptions and one or two insights to a mathematical proof?

I'd say a Zettlekasten user would agree with you if you mean 1

The point, I believe, was that the more you remember, the better you can think. As in you should strive to remember stuff, and not just be lazy and rely on LLMs. I agree with that.

> So, coming back to the initial starting point that “you don’t have to remember anything”. The opposite is true. You have to remember EVERYTHING.

I see it like this: it is absolutely wrong to think that you don't have to remember anything. In fact, ideally you would remember everything. The more you remember, the better you can think. Now in practice, it's impossible to remember absolutely everything, so we should strive to remember as much as we can. And of course we need to be clever in how we select what we remember (but that seems obvious).

The point is really that it is common to say "it's useless to remember it because you can ask your calculator or an LLM", and the article strongly disagrees with that.

And the more experience with computers I get, the more I realize that there's actually not that many pure unique and mutually orthogonal _concepts_ in computer science and software engineering. Yes, a competent engineer must know, feel, live these concepts, and it takes a lot of work and exposure to crystallize them in the brain from all the libraries, books, programs, architectures one has seen. But there's not a lot of them! And once you are intimate with all of them, you can grok anything computer-related quickly and efficiently: because your brain will just wuickly find the "coordinates" of that thing in the concept space, ans that's all you'll have to understand and recall later.

IMO, this is the whole point of the article: AI tools "help" a lot when we are completely uninformed. But in doing that, they prevent us from getting informed in the first place. Which is counter-productive in the long term.

I like to say that learning goes in iterations:

* First you accept new material (the teacher shows some mathematical concept and proves that it works). It convinces you that it makes sense, but you don't know enough to actually be sure that the proof was 100% correct.

* Then you try to apply it, with whatever you could memorise from the previous step. It looked easy when the teacher did it, but when you do it yourself it raises new questions. But while doing this, you memorise it. Being able to say "I can do this exercise, but in this other one there is this difference and I'm stuck" means that you have memorised something.

* Now that you have memorised more, you can go back to the material, and try to convince yourself that you now see how to solve that exercise you were stuck with.

* etc.

It's a loop of something like "accept, understand, memorise, use". If, instead, you prompt until the AI gives you the right answer, you're not learning much.

That might be a good criteria for how much to memorize: do you want to be able to do it live?